Multi-Hyb: A Hybrid Algorithm for Solving DisCSPs with Complex Local Problems

Abstract

A coarse-grained Distributed Constraint Satisfaction Problem (DisCSP) is a constraint problem where several agents, each responsible for solving one part (a complex local problem), cooperate to determine an overall solution. Thus, agents solve the overall problem by finding a solution to their complex local problem which is compatible with the solutions proposed by other agents for their own local problems. Several approaches to solving DisCSPs have been devised and can be classified as systematic search and local search techniques. We present Multi-Hyb, a two-phase hybrid algorithm for solving coarse-grained DisCSPs which uses both systematic and local search during problem solving. Phase 1 generates key partial solutions to the global problem using systematic search. Concurrently, a penalty-based local search algorithm attempts to find a global solution to the problem using these partial solutions. If a global solution is not found in phase 1, the information learnt from phase 1 is used to inform the search carried out during the next phase. Phase two runs a systematic search algorithm on complex variables guided by the following knowledge obtained in phase 1: (i) partial solutions and; (ii) complex local problems which appear more difficult to satisfy. Experimental evaluation demonstrates that Multi-Hyb is competitive in several problem classes in terms of: (i) the communication cost and (ii) the computational effort needed.