Feasibility Restoration for Iterative Meta-heuristics Search Algorithms

Authors:
Marcus Randall
Affiliations:
-
Venue:
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Year:
2002

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Abstract

Many combinatorial optimisation problems have constraints that are difficult for meta-heuristic search algorithms to process. One approach is that of feasibility restoration. This technique allows the feasibility of the constraints of a problem to be broken and then brought back to a feasible state. The advantage of this is that the search can proceed over infeasible regions, thus potentially exploring difficult to reach parts of the state space. In this paper, a generic feasibility restoration scheme is proposed for use with the neighbourhood search algorithm simulated annealing. Some improved solutions to standard test problems are recorded.