Contemporary systems of Guaranteed Delivery (GD) advertising work with two different stages, namely, the offline selling stage and the online serving stage. The former deals with contract allocation, and the latter fulfills the impression allocation of signed contracts. Existing work usually handles these two stages separately. For example, contracts are formulated offline without concerning practical situations in the online serving stage. Therefore, we address in this paper a bi-objective contract allocation for GD advertising, which maximizes the impressions, i.e., Ad resource assignments, allocated for the new incoming advertising orders, and at the same time, controls the balance in the inventories. Since the proposed problem is high dimensional and heavily constrained, we design an efficient local search that focuses on the two objectives alternatively. The experimental results indicate that our algorithm outperforms multi-objective evolutionary algorithms and Gurobi, the former of which is commonly applied for multi-objective optimization and the latter of which is a well-known competitive commercial tool.