A survey of solving approaches for multiple objective flexible job shop scheduling problems

Abstract

Many real life scheduling problems can be formulated as Flexible Job Shop Scheduling Problems (FJSSPs) which simultaneously optimize several conflicting criteria. A typical feature of such problems is their high computational complexity. The purpose of this paper is to provide a review of the techniques, developed to solve multiple objective FJSSPs during the last decade. These techniques could be classified into two groups: approaches with application of mathematical models and heuristic approaches. Usually hybrid metaheuristic algorithms are proposed for large dimensional real life problems and they outlay the tendency for the future developments of efficient solution approaches for multiple objective FJSSPs.