This study proposes a multi-agent-based simulation and optimization framework to enhance phased evacuation strategies by integrating fire dynamics, evacuees’ characteristics, and evacuation processes. Unlike conventional models, this framework probabilistically assesses the integrated effects of heat, asphyxiant gases, and irritant gases on different evacuees’ incapacitation. The Non-dominated Sorting Genetic Algorithm III (NSGA-III), coupled with a trained neural network, is employed to find optimal phased evacuation strategies considering the Total Evacuation Time (TET), congestion, and fire impact. To assess its effectiveness, the framework is applied to a fire scenario in an educational building, comparing simultaneous and phased evacuation strategies. Results demonstrate that the selected phased evacuation strategy significantly enhances evacuation efficiency, reducing TET, congestion, and fire impact by 14.8%, 33.3%, and 13.1%, respectively. These findings underscore the framework’s potential for improving fire evacuation planning, providing a simulation-based approach to optimizing evacuation strategies and enhancing safety in fire.

The inverse analysis of the graph model for conflict resolution (GMCR) determines the preferences required to ensure that a desired resolution is an equilibrium. However, existing studies have yet to examine the transition mechanism from the current state to the desired resolution. To address this issue, this study introduces an integrated minimum cost conflict mediation path (I-MCCMP) model within the GMCR framework. This model not only identifies the necessary preferences to establish the desired resolution as an equilibrium but also determines the optimal conflict mediation path to achieve it. To demonstrate its applicability, the proposed model is applied to the real-world Lake Gisborne Conflict.

In the context of severe global warming, accurately exploring the trend of carbon emissions intensity (CEI) changes is of great significance for mitigating climate change issues. The implementation of China's Carbon Emissions Trading Scheme (ETS) in 2013 is a policy intervention aimed at influencing CEI. The impact of intervention events makes forecasting a complex problem, which poses significant challenges to the construction of forecasting models. We first develop a quadratic time-varying nonlinear discrete grey model (QDNDGM(1,1)) to assess the intervention effect of the ETS policy. Then, a novel intervention effect-based quadratic time-varying nonlinear discrete grey model (IE-QDNDGM(1,1)) is developed to conduct the prediction under intervention effect, including an intervention term. The Whale Optimization Algorithm (WOA) is used to calculate a nonlinear parameter. We assess the intervention effect of the ETS policy in China and find that it can indeed reduce CEI. We verify the IE-QDNDGM(1,1) model’s superiority by comparing its predictive performance with that of three grey models, one statistical technique, and one artificial intelligence model. The comparative study shows the proposed model’s excellent fitting and prediction performance. An ablation experiment is conducted to validate the design of the IE-QDNDGM(1,1). Policy implications of the ETS intervention effect are discussed.

An evacuation navigation model incorporating a fire's detrimental effect on evacuees' escape capability is presented. Fire is one of the most common hazards in buildings that severely impacts evacuees' escape capability. A fire dynamics model is used to simulate dynamics of a fire at various locations in a building. An index, called Capability Deterioration Rate (CDR), is introduced to model how fire effluents, such as smoke, heat, and toxic gases, impact escape capability spatiotemporally. This index is incorporated into a modified Dijkstra algorithm by changing weights of navigation edges. An agent-based model taking into account the fire dynamics and escape capability is used to simulate an agent's evacuation from a location to minimize the total travel cost from the location to an egress door. A three-floor building is used as a case study to demonstrate the application and effectiveness of the proposed model. The proposed model can be used to evaluate and select the best navigation plan in terms of escape capability under various fire scenarios.

Abstract Tensor singular value decomposition (t‐SVD) provides a novel way to decompose a tensor. It has been employed mostly in recovering missing tensor entries from the observed tensor entries. The problem of applying t‐SVD to recover tensors from limited coefficients in any given ortho‐normal basis is addressed. We prove that an n × n × n 3 tensor with tubal‐rank r can be efficiently reconstructed by minimising its tubal nuclear norm from its O ( rn 3 n log 2 ( n 3 n )) randomly sampled coefficients w.r.t any given ortho‐normal basis. In our proof, we extend the matrix coherent conditions to tensor coherent conditions. We first prove the theorem belonging to the case of Fourier‐type basis under certain coherent conditions. Then, we prove that our results hold for any ortho‐normal basis meeting the conditions. Our work covers the existing t‐SVD‐based tensor completion problem as a special case. We conduct numerical experiments on random tensors and dynamic magnetic resonance images (d‐MRI) to demonstrate the performance of the proposed methods.

A survey of the design, development and implementation of a flexible decision technology called the graph model for conflict resolution (GMCR) is discussed for systematically investigating real world conflicts within a system of systems engineering outlook. This encompassing GMCR methodology has been constructed during the past three decades by the authors, their colleagues and students from many countries for addressing a rich range of conflict situations. GMCR can be used for studying large and small conflicts and includes methods for preference elicitation, preference uncertainty (unknown, fuzzy, grey numbers and probabilistic). Many kinds of definitions exist for possible human behavior under pure competition which can be transformed for utilization in coalition analysis. GMCR can handle emotions, attitudes, and misperceptions. Within inverse GMCR, one can calculate the preferences needed by decision makers (DMs) to reach a desirable equilibrium. Under behavioral GMCR one can ascertain the strategic thinking of DMs when the input and output are known. Decision support systems can be built for implementing the array of GMCR advancements. Future expansions of GMCR can be guided by key characteristics of actual disputes. Artificial intelligence (AI) GMCR is a promising subfield of study within GMCR.

Hesitant fuzzy preference relations (HFPRs) are formally proposed to model the conflict situation in which each decision maker (DM) consists of multiple individuals and each individual has its own fuzzy preferences over the feasible states within the framework of the graph model for conflict resolution (GMCR). Based on HFPRs, new definitions for hesitant fuzzy Nash stability, hesitant fuzzy general metarationality, hesitant fuzzy symmetric metarationality, and hesitant fuzzy sequential stability permit stability analyses to be carried out. Moreover, a new option prioritization technique, called hesitant fuzzy option prioritization, is developed for modeling a DM’s HFPRs based on the DM’s priority sequence of preference statements, the DM’s fuzzy truth values and levels of confidence. The groundwater contamination conflict of Elmira, Ontario, Canada, is utilized as a case study to illustrate the usefulness and applicability of the hesitant fuzzy option prioritization technique and GMCR with HFPRs.

Mixed coalition analysis approaches are developed within the framework of the graph model for conflict resolution (GMCR) for analyzing the heterogeneous multicoalitional opponents having mixed coalitional sanctions, in which some sanctioning coalitions may only invoke coalitional improvements (CIs) while others may go to any reachable states to jointly sanction a focal coalition's CIs. To accomplish this, the concept of a full coalition set is defined in which each participating decision maker (DM) is represented once either as an individual player or part of a coalition. All possible scenarios in which a full coalition set could be formed is called the universal coalition set. When calculating the stability of a specific state for a particular coalition in a given conflict, the remaining DMs form the universal coalition set whose moves have the potential to block any CIs by the focal coalition within four specified solution concepts having full participation of sanctioning opponents. To handle heterogeneous opponents with mixed CIs (MCIs), the mixed coalition analysis approach is proposed, which provides a more general coalition analysis framework than existing coalition analysis approaches. Moreover, the interrelationships among coalitional stabilities and mixed coalitional stabilities with full participation are investigated followed by their corresponding matrix representations which can significantly improve their computational efficiency and make the computer implementation possible. Finally, a case study is investigated to demonstrate how to employ the proposed mixed coalition analysis approaches to address a real-world environmental conflict.

A new hybrid preference framework of the graph model for conflict resolution (GMCR) is proposed which allows decision makers (DMs) having both unknown preference and fuzzy preference to be taken into account in conflict modeling and analysis. The novel hybrid preference structure provides DMs with a more flexible technique to express preference. It is capable of covering the unknown preference of one feasible state over another, as well as fuzzy preference. Moreover, within the new hybrid preference structure, four extension forms of unknown preference are defined for different fuzzy stability definitions. These stability definitions under the new hybrid preference can be employed to thoroughly investigate complex conflicts existing in practical applications, and can offer enhanced strategic insights regarding the conflicts. A specific real-world water diversion conflict occurring in China, which includes multiple DMs and hybrid preference, is utilized to investigate how the new hybrid preference framework of the GMCR can be conveniently applied in practice.

A system of systems (SoS) framework is proposed to describe the complex interactions among water, energy and food systems. Through the investigation of the key interconnections among the three systems, improving water use efficiency is considered as one entry point for this framework. Implementation steps of the framework are explained in detail. From an SoS perspective, meaningful insights for policy-making can be garnered for enhancing the security level of water, energy, and food systems at regional or national scales.

Using the observed or desired stability results of each decision maker (DM) and the equilibrium of a conflict, an algorithm is proposed that determines whether the Nash, general metarationality, symmetric metarationality or sequential stability definition best explains the observations or how to achieve the desired equilibrium. The matrix representation of the graph model for conflict resolution, normally used to determine stabilities that reflect different models of human interaction in conflict, is utilized here to keep track of available one-step moves for each DM, as well as the DMs' relative preferences among states. A key theorem involving matrix representation of graph models determines which stability types are consistent with the observations or achievement of the desired equilibrium, taking into account specified preferences of the DMs, for the case of two or more DMs. To illustrate the use of the algorithm in practice, behavioral analysis is applied to a softwood lumber dispute between Canada and the USA.

A new technique is introduced to model misperception by participating decision makers (DMs) in a conflict having two or more DMs within the framework of the graph model for conflict resolution. This comprehensive approach enables one to model a conflict situation involving misperception: held by and about the focal DM and its opponents. To achieve this, DMs' options in a conflict situation are classified based on different kinds of misperception that can alter the choices of the focal DM and/or the other DMs. Furthermore, the combination of DMs' options can generate the universal set of options for the entire conflict, which can then be used to construct the universal set of states. This novel design can differentiate between the states that are recognized by all DMs and those that are recognized individually. Furthermore, eight sets of equilibria are formally defined within the construction of the first-level hypergame in graph form to provide strategic insights into the conflict and reflect the effect of DMs' misperceptions on the equilibria of the dispute.

A new hybrid preference framework of the Graph Model for Conflict Resolution (GMCR) is proposed to facilitate modeling and analysis of conflicts involving two decision makers (DMs) with fuzzy levels of preference. The new preference structure, a hybrid of models of three-level strength of preference and fuzzy preference, provides a more flexible technique to express DMs' relative preferences among states, and is more comprehensive and flexible than existing models. One key contribution of this paper is to extend four graph model stability definitions for fuzzy preferences, consisting of fuzzy Nash stability (FR), fuzzy general metarationality (FGMR), fuzzy symmetric metarationality (FSMR), and fuzzy sequential stability (FSEQ), to the new hybrid preference structure. This extension permits the analysis of the hybrid model, including both strong and weak stabilities. The resulting modeling and analysis system can be applied to complex two-decision-maker conflicts, thereby enhancing the ability of the graph model to provide strategic insights. A specific two decision-maker conflict is utilized to illustrate the practical application of the new hybrid preference framework for GMCR.

The 1956 nationalization of the Suez Canal dispute, between Egypt and an alliance between the United States (US) and Britain, is modeled and analyzed within the paradigm of a first-level hypergame in graph form. The results reveal that Britain and US encountered a strategic surprise in the dispute on account of their failure to predict Egypt's action in nationalizing the Suez Canal. The equilibrium states of the dispute are analyzed to provide insights into the types of the misperceptions that caused the conflict, the possible decision makers' reactions after observing the equilibrium states, and the sustainability of the first-level hypergame equilibria. The analysis reveals substantial motivation for the United States and Britain to intensify the dispute to recapture the Suez Canal and to improve their situation.

Multiple criteria decision analysis with action interdependence is presented of potential investments for the aviation industry to reduce greenhouse gas (GHG) emissions. The aviation industry has an interest in increased efficiency due to political and public pressure to reduce GHGs, and a finite fuel supply that will lead to increased costs. This analysis utilizes four criteria (return on investment, carbon dioxide (CO2) emissions, minimal disruption, and popularity) to evaluate combinations of actions. Possible interdependencies between any two actions are also taken into account. This paper ascertains that the use of algae bio fuels and high bypass engines are the most preferred actions based on the synergistic interdependence between these two actions. The results of the study are supported by the preferences of the aviation industry as described in public releases.

The impact of a water demand management plan on water users is investigated within a comprehensive cooperative water allocation model. A demand management plan is specified and incorporated into the two-step multi-period fair water allocation model. The results indicate that cooperation can yield more net benefits, and a water demand management plan is able to lead to a further increase of the aggregated net benefits. The additional net benefits can be fairly allocated among users by using a modified cooperative game. Fair sharing of additional net benefits provides a motivation for water users to implement a water demand management plan, and eventually to achieve a more productive water management.

The standard graph model for conflict resolution is enhanced to model misperception of options and preferences. In particular, misperception caused by unknown options by one or more decision makers (DMs) is formally defined in the modified graph model framework. Moreover, DMs' preferences are expressed in a relative fashion by pairwise comparisons among any pair of states. That is, the modified graph model can handle both transitive and intransitive preference structures. Furthermore, three sets of equilibria are defined within the modified graph model, namely, steady, unsteady, and stealthy equilibria. The aim of identifying equilibria sets is to ascertain the first level hypergame equilibria for the modified graph model. The 2011 conflict between North and South Sudan over South Sudanese oil exports is studied using the modified graph model to illustrate the applicability of the model and to gain better insight into and understanding of the dispute.

The risk of a project portfolio is assessed using a new methodology that identifies the risk transfer in projects by using a Bayesian network structure learning algorithm to construct an interdependent network of risks. In particular, to overcome the drawback of a greedy search algorithm having a random starting structure, the mutual information between project risks is measured before executing the algorithm by computing the impact of technical interactions on project risks. It is demonstrated that the preprocessing can exclude the error and indistinctive connections, so as to reduce the search space effectively. Finally, the project portfolio risk of a practical case is assessed using this method, and the results show that the interdependent network of risks is an effective tool to reveal the risk transfer in projects and infer the value of project portfolio risk.

A fair water allocation model is utilized to assess the impact on stakeholders of a water demand management plan. Moreover, an asymmetric Nash bargaining model is employed to analyze sharing of the additional net benefits gained among stakeholders. The results indicate that the performance of a water system with water demand management strategies is better in terms of lower water shortage ratios and greater economic benefits. Moreover, the environmental requirements could be better met when water demand management is implemented. The additional benefits gained can be shared by stakeholders through a bargaining process. The results of the asymmetric Nash bargaining analysis are presented.

A novel agent-based framework for modeling and simulating competitive and cooperative behavior under conflict is proposed. Formal definitions of Nash, general metarational, symmetric metarational, and sequential stability decision rules reflecting human behavior under conflict are presented in this paper. The definitions are inspired by the solution concepts of the graph model for conflict resolution and are conceived for implantation in the proposed agent-based modeling and simulation framework. With these decision rules, competitive and cooperative conflict dynamics are simulated for a theoretical common-pool resources dilemma. Moreover, policies can be tested for their effectiveness in avoiding or recouping from a tragedy of the commons.

A systems methodology for generating ordinal preferences from a value system is presented in this paper. The methodology employs value-focused thinking, the analytic hierarchy process, and a variety of methods, such as criteria-satisficing, optimizing, prioritization and weighting, to capture different value judgments. The methodology is operationalized for integration with the graph model for conflict resolution, which facilitates modeling and analysis of strategic conflicts. In applying the proposed methodology, preferences take into account evolving contextual variables in order to simulate participants' responses in a dynamic environment. The effects of different value systems on preferences and resulting conflict dynamics are demonstrated for a theoretical common-pool resources dilemma.

A novel approach based on the graph model for conflict resolution (GMCR) methodology is proposed to address the problem of multistakeholder system portfolio decision analysis encountered in architecting a system of systems (SoS) with desired capabilities. More specifically, a flexible four-process framework for capability-based SoS architecting containing interactive portfolio decision analysis to promote multistakeholder design negotiations on system portfolio selections is presented. By taking full advantage of the inherent realistic and flexible design of the GMCR paradigm, an interactive portfolio decision analysis approach is designed to facilitate the systematic modeling and analysis of system portfolio decisions at the SoS level in order to achieve potential compromises among all key stakeholders having disparate preferences and interacting according to different conflict behavior patterns. This approach permits the prediction of possible mutually agreeable system portfolios for SoS architecture development. Last, the feasibility of the proposed approach is demonstrated using an illustrative example.

The negotiations over reducing the amount of greenhouse gas (GHG) emissions among major emitters are studied using the Graph Model for Conflict Resolution to gain better insight and understanding into the current situation. After the Durban and Doha climate change conferences were signed, major emitters took different mitigation actions to lower the amount of GHG in the atmosphere. The possible equilibrium states were determined to ascertain if major GHG emitters would lower their emissions according to the agreements or not. The analytical results reveal a strong motivation from the European Union nations (EU 27) and other developed countries to lower the amount of GHG with high ambition levels, while both the United States (US) and emerging countries namely, China, India, Brazil and South Africa, are acting with low ambition levels to lower the amount of GHG. The analysis also indicates that both the EU 27 and other developed countries will lower their ambition levels if the US and emerging countries retain low ambition levels. Finally, the analysis also demonstrates that both the US and China are still not willing to cooperate with each other to mitigate negative impacts of climate change.

A methodology to construct ordinal preferences from multiple objectives for multiple participants in a conflict is proposed. The methodology combines value focused thinking, the analytic hierarchy process, criteria satisficing, and relative weighting and prioritization schemes to order states of a conflict. Compared to conventional methods of utility and optimization, application of the proposed methodology is less expensive, both cognitively and computationally. Still, hard thinking and value judgments would nonetheless be required to define meaningful and appropriate objectives, attributes and criteria, as would any decision making task. Preference construction for an 8-participant conflict is demonstrated. The resulting preferences can be directly inputted into a graph model for conflict resolution to determine stable outcomes of the conflict.

The Yonmenkaigi System Method is utilized for developing a collaborative action plan for community recovery of a disaster damaged village. A case study was carried out in the Garisan-ri community, County of Inje, Province of Gangwon, Korea. The case study demonstrates how residents who experienced the flood disaster in 2006 in their local community can collaboratively create an action plan for their community recovery. The Yonmenkaigi System Method, originally developed in a local community in Japan, has the following main steps: defining the main theme based on SWOT analysis, working on a Yonmenkaigi chart, debating to improve the consistency and quality of collaborative activities, and presenting the group action plan.

The ongoing conflict among Shiites, Sunnis, and the Government of Bahrain is formally investigated using the graph model for conflict resolution in order to gain strategic insights into how this festering dispute can be better understood and resolved. At the modeling stage, the Bahrain conflict is meaningfully described in terms of the three main decision makers (DMs), as well as each DM's options or courses of action it controls and relative preferences among the possible states or scenarios that could arise. Subsequently, at the analysis stage, a stability analysis is carried out to determine the stability of a state from each DM's viewpoint, according to different descriptions of behavior under conflict, as well as the equilibria or compromise resolutions. The findings indicate that although the present strife could continue unless the Government steps down, a compromise solution in which the Government institutes reform is possible.

The Sandankai System Method is utilized for disaster education to improve communication of disaster risk at the community level. A case study was carried out in the Samcheok High School, City of Samcheok, Gangwon Province, Korea. The case study demonstrates how students who experienced the disaster in 2002 in their local community can create disaster scenarios and collaboratively develop an action plan for their community. The Sandankai Method consists of the following steps: definition of the major premises of the disaster situation, development of disaster scenarios and an action plan by completion of a Sandankai chart, collaborative discussion among members of each group, and presentation of the disaster scenarios and action sub-plan of each group. The Sandankai chart has three time-phases: within one to two days, within one to two weeks and within one to two months, after a disaster.

A meta-heuristic based negotiation algorithm is proposed to resolve conflict over the Waste Load Allocation (WLA) problem in rivers. In the proposed approach, the waste dischargers are allowed to negotiate with each other using Ant Colony Optimization (ACO) and decide how much they plan to discharge while strictly meeting the environmental standards at the checkpoints. The proposed algorithm is applied to solve two mathematical benchmark problems. Moreover, the approach developed is used to study an illustrative WLA problem.

A systems approach to integrative adaptive management of brownfields on Alberta's oil sands development sites is presented. In particular, the Graph Model for Conflict Resolution (GMCR) is utilized to understand underlying development conflicts among stakeholders, which arise due to competing economic, environmental and societal objectives. The conflict model provides a formalized hypothesis-testing platform for determining responsible policies, which are those that enhance integrative adaptive management in order to utilize this resource responsibly.

The Yonmenkaigi system method is utilized for developing a collaborative action plan for disaster risk mitigation at the community level. A case study carried out in the Shuhachi community, City of Kyoto, Japan, demonstrates how residents who are interested in disaster reduction in a local community can collaboratively develop an implementable action plan for their community. The Yonmenkaigi system method has the following main steps: carrying out a SWOT analysis, completing a Yonmenkaigi Chart, debating between groups, and presenting the group action plan. Relationships of the debated action plan components are analyzed by using the Interpretive Structural Modeling (ISM) method. For the case study, the core action plan component which is the root to achieving the action plan is identified.

Aid coordination processes for post-disaster education in Indonesia after the 2004 Indian Ocean Tsunami tragedy are modeled and analyzed. Stakeholders who shared the same mission for disaster risk mitigation gradually started to work together. Three models of the value creation process generated by the aid coordination, value provision, adaptive value, and co-creative value models, are presented. Human social networks and consortia of consultation are helpful in building trust relationships among participants, enabling them to mutually collaborate and ultimately create a new aid coordination form to promote post-disaster education.

The uncertainties associated with liability in brownfield redevelopment and relevant risk management tools are discussed based on a comparative review of the situation in Canada and the United States. The changes of regulations and policies, inherent uncertainties of site assessment and remediation techniques, incidents of contaminant transport and exposure, and variations of economic and financial conditions all lead to the uncertainties of environmental liability. The fear of liability especially the associated uncertainties is the key obstacle for owners or developers to undertake cleanup and redevelopment due to the subsequent unpredictability of economic profitability. Various risk management tools have been gradually developed in the last three decades to address liability uncertainties, both within Canada and the US, among which environmental insurance and innocent owner's shelter from liability are the two most viable instruments to reduce the fear of liability. Policy making and risk management have evolved more slowly in Canada than in the US and there is a trend for Canadian provinces to adopt the successful policies and tools used in the US rather than formulate their own.

An approach to model and quantify a user’s Web search interests using the user’s navigational data is presented. The approach is based on the premise that frequently visiting certain types of content indicates that the user is interested in that content. The proposed approach can be divided into three steps: monitoring the user’s navigational data; using the cumulative weight to determine a Web page’s content; and employing the Naïve Bayes Model for updating the user’s interest model. In order to demonstrate the effectiveness of the proposed model, experimental software is developed to analyze a user’s interests in sports. The experimental results demonstrate that the approach can effectively model the user’s interest. The proposed model could be integrated with personalized Web services.

An intelligent agent-based mobile phone supply chain simulation system is developed, in which a business entity or customer is represented by an intelligent agent. The proposed simulation system has six layers - raw material providers, component manufacturers, product assemblers, product holders, retailers, and final customers. There are two agents in each layer. An agent has a number of engines to implement various functions of the agent. This system can simulate many activities of a business in a supply chain either automatically or manually. The system can be used to study and simulate supply chain management technologies and methodologies.

Two different approaches to conflict analysis are applied to the serious conflict arising over the illegal dumping of toxic waste in the former capital of Ivory Coast in August 2006, in order to compare their capabilities for gaining strategic insights into this dispute. More specifically, the Graph Model for Conflict Resolution and Drama Theory are employed to systematically study the toxic waste controversy. Subsequently, these two techniques are compared using this conflict with respect to their intrinsic and actual capabilities for modeling, better understanding and forecasting the equilibria or potential resolutions.

An intelligent agent-based supply chain simulation system is designed, in which a supply chain entity is represented by an agent. There are six layers in this system: raw material providers, component manufacturers, product assemblers, product holders, retailers, and final customers. A detailed agent structure is presented and various functions of the agent are described. Moreover, communication activities among agents are discussed. By using the proposed system, issues in supply chain integration, information sharing among supply chain partners, demand forecasting, supply chain risk management, and automated communication and negotiation, could be simulated and studied.

A game-theoretic approach to brownfield redevelopment is presented to support negotiations on related cost and benefit allocation. The process of brownfield redevelopment is discussed and three types of key decision makers (DMs) are identified, namely the landowner, the developer and the government. Based on a qualitative analysis of coalitions among the key DMs, a cooperative game model is formulated for the brownfield redevelopment cost and benefit allocation problem. To initiate the negotiation on the cost and benefit allocation, a common understanding of the estimates of relevant costs and benefits in a brownfield redevelopment project is required. The proposed modeling framework utilizes various nucleolus concepts and the Shapley value to find alternative fair cost and benefit allocations from which the DMs can make the final selection. An illustrative example is used to demonstrate the application of the proposed approach.

A policy equilibrium is defined, and its properties investigated, for conflicts with more than two decision makers (DMs). A fundamental construction is the metarational tree, which expresses DMs' interactions as sequences of rounds, each consisting of an initial move by the focal DM followed by countermoves by the opponents. Using the metarational tree, the stability definitions of the graph model for conflict resolution can be adapted to apply to policies. These generalized metarational stabilities are shown to generalize Nash, general metarational, and symmetric metarational stabilities. Relationships among generalized metarationalities are derived, as are their connections with policy equilibria. Finally, the refinement that allows only credible moves (moves that are in the immediate interest of the mover) produces a new family of credible generalized metarational stabilities that generalizes the concept of sequential stability in the graph model.

Two multiple objective optimization methods for water rights allocation, the priority-based maximal multiperiod network flow programming (PMMNF) method and lexicographic minimax water shortage ratios (LMWSR) method are applied to the South Saskatchewan river basin in southern Alberta, Canada. Population growth and economic expansion are straining water resources in this basin. Irrigation, municipal and industrial uses, and hydropower generation are the major water demands competing for limited water resources. The case study shows that the PMMNF method usually produces large differences in the satisfaction ratios among uses in times of water shortages since it is based on the priority concept. On the other hand, the allocations by LMWSR lead to fairer distributed satisfaction ratios because it adopts the lexicographic minimax equity concept and thus has water shortages shared among all the water demands of various types of uses.

An online iterative combinatorial auction system called OICAS is designed and developed. The system can be used to auction multiple items each with a single unit simultaneously and a bidder can bid any bundle of items. A new auction mechanism, called the ascending revenue mechanism, and a novel winner determination algorithm are proposed. Unified Modeling Language (UML) models are developed for describing the system. A prototype of OICAS is implemented using Visual Basic and Microsoft Access. Computational testing shows that this system is fast enough to be used online.

A new preference structure is introduced into the graph model for conflict resolution. This structure can handle a decision-maker's (DM) strict preference for one state or scenario over another, equal preference for states, and uncertain or unknown preference in the comparison of two states. Built upon this preference structure, four types of solution definitions modeling human behavior under conflict are extended to accommodate uncertainty in preferences. Four distinct ways to consider uncertain preference information are identified, producing sixteen extended stability definitions. Interrelationships of these definitions within and across the four definition sets are investigated. Illustrative examples of two-DM and multi-DM conflict models are presented to show how the new solution concepts can be applied in practice.

A comprehensive methodology is developed to achieve equitable, efficient and sustainable water allocation in a river basin. Water allocation is carried out in two steps: (1) allocation of initial water rights to water stakeholders and users based on existing water rights systems or agreements; and (2) reallocation of water and net benefits through water transfers to promote equitable cooperation of all stakeholders in a river basin and to achieve efficient use of water. Three methods, prior water rights, modified riparian water rights and lexicographic minimax demand shortage ratios, are proposed for the equitable initial water rights allocation. Using cooperative game theory carries the associated water transfers and net benefit reallocation.

The concept of a policy is developed within the framework of the graph model for conflict resolution. More specifically, a policy is defined as an action plan from every possible state in a conflict for each player. A state forms what is called a policy stable state (PSS) if every player in a game does not prefer to move to another state given the other players' policies. The policies that cause a PSS constitute a policy equilibrium. Moreover, a refinement to PSS is suggested in order to take into account credible responses by players. Relationships with existing stability concepts in the graph model for conflict resolution are explored.

A comprehensive decision support system, GMCR II, is developed for the systematic study of real-world interactive decision problems. Model formulation is presented in Part I, and analysis and output interpretation in Part II. GMCR II is based upon existing and new research developments of the graph model for conflict resolution. In Part I, specially designed data structures and corresponding algorithms are implemented for generating and representing possible states, removing infeasible states, coalescing indistinguishable states, and specifying and storing allowable state transitions. Algorithms implementing different approaches to the elicitation of preferences over states enable GMCR II to construct and manage an efficient, flexible, and complete graph model of a strategic conflict.

For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.

A new approach to dynamic conflict analysis is presented that integrates value-focused thinking and the graph model for conflict resolution. This approach is based on the premise that values are the driving forces behind the evolution of a conflict from one frame to another. Value-focused thinking is employed to identify the decision makers' values and objectives, which facilitate the establishment of a conflict model consisting of decision makers as well as each decision maker's options and preference rankings of states for each frame. A decision support system called GMCR II is utilized to analyze the conflict model and predict possible resolutions for each frame, which are assessed against the measures established from value-focused thinking for evaluating the achievement of objectives. A case study is presented to illustrate how the approach can be applied to a real world conflict.

Four types of solution concepts for modeling human behavior under conflict are defined to accommodate uncertainty in preferences. For a given decision-maker participating in a conflict the preference structure includes components to handle strict preference of one state over another, equal preference between states, and uncertainty or unknown preference when comparing two states or scenarios. Four distinct ways to incorporate uncertain preference information into the four types of solution concepts are considered and the "sustainable development game" is used to illustrate how the new solution concepts can be applied in practice and strategic insights that can be garnered.

Conflicts associated with fisheries are common and frequently attract significant public attention given the economic and social importance of this sector to coastal communities. The introduction of species-at-risk legislation, clarification of First Nations (aboriginal) fishing rights, globalization, and changing public expectations with respect to conservation and sustainability have significantly complicated the problem of conflict resolution. A number of examples of fisheries conflicts are described, and approaches to resolving them are discussed. Then the recent salmon aquaculture conflict in British Columbia, Canada is examined within the framework of the graph model for conflict resolution. The graph model permits the consideration of how parties in the conflict may strategically interact with one another as a consequence of each party selecting from the options under its control. The participants adopt relative preferences among the possible states or scenarios a priori and in response to the actions taken by other players in the conflict. The relative stability of different solutions provides useful insights into the behavior of the participants and the likelihood of future conflicts.

A new perspective in infrastructure management is put forward whereby institutional arrangements and physical facilities, as well as parts of the natural environment, are systematically coordinated to serve the common needs of different stakeholders in society in a sustainable fashion. Moreover, it is explained how emerging issues in infrastructure management can be properly addressed within this novel framework. One pressing issue, for example, is how to encourage cooperation and perhaps consensus among divergent stakeholders who envision different alternatives to infrastructure development, management and renewal. To facilitate conflict resolution, a range of techniques designed for handling multiple participant-multiple criteria problems are suggested.

The implementation and testing of a case-based reasoning system for conflict resolution is presented. The issues of case representation, case storage, case retrieval and case reuse are considered. Information on 104 conflict cases that have been analyzed using a methodology called the graph model for conflict resolution is collected and stored. The system is first tested and verified using the case base and then the system's ability to retrieve similar cases is evaluated.

The graph model for conflict resolution is put forward as a valuable service tool for providing strategic advice in multiple participant-multiple objective decision making situations. An international trading conflict over the sale of Canadian softwood lumber to customers in the United States is employed for demonstrating how the decision support system GMCR II can be utilized by managers and consultants for better understanding a conflict and its strategic implications. The objective is to furnish clients with insightful advice on how to make sage decisions within a competitive economic environment.

Meaningful connections among different types of decision making Situations are established in order to improve the development of useful decision technologies for application to real world problems. More specifically, an assertion is put forward that suggests that single participant-multiple criteria (SPMC) and multiple participant-single criterion (MPSC) decision making problems may be treated in essentially the same way. In this way, decision technologies that are already available can be suitably refined for use in studying both SPMC and MPSC decision situations. Another assertion is made that a multiple participant-multiple criteria (MPMC) decision situation can be converted to a MPSC decision situation. In order to simplify the explanation, illustrative applications are utilized throughout the paper. Finally, worthwhile directions for future research are summarized.>