Many real-world problems involve allocating limited resources to multiple consumers with dissimilar objective functions. Current techniques usually aim to maximize some single weighted sum performance metric, which fails to properly take into account these dissimilar objectives. This research investigates the Multi-Player Game Approach, modeling the problem as a multi-player competitive cum collaborative game where each consumer is a player in the game. It is played in several iterations of bidding, arbitration and negotiation phases. In the bidding phase, the consumers bid for resources using their own customized strategies. In the arbitration phase, resources are allocated to the consumers based on the bids tabled. In the negotiation phase, the consumers attempt to make mutually beneficial trades with each other. Experiments on the university examination timetabling problem suggest that this approach may outperform centralized approaches.