Finding Efficient Schedules in Multi-Entity Negotiation

Efficient scheduling for potential negotiations that could be initiated among interacting business parties is crucial to satisfy the embedded time or budget constraints that parties might have. An efficient schedule should guarantee the maximum possible utility to all parties taking into account the correlations or inter-dependencies that exist among different negotiable entities. In this project we address the problem of scheduling negotiation over multiple entities in both deterministic and probabilistic settings. We study the problems involved in these settings from both data management and game theory perspectives, and propose a set of heuristic measures and search algorithms to solve the problem in different scenarios. We validate our proposed methods by an extensive experimental study performed on synthesized data sets generated from GAMUT[9] test suite.