Meta-heuristics approaches for the flexible job shop scheduling problem

Abstract

All along more than two decades of research, the flexible job shop scheduling problem incarnated combinatorial optimization problem’s intractability in its harder sense and motivated the investigation of an important number of meta-heuristic approaches as an effective issue for its resolution.This chapter addresses the potentialities of various metaheuristics approaches for solving a linearized form of the multi-objective FJSSP.It attempts particularly to present most important conceptual issues related to the application of common representative instances of meta-heuristic search approaches to the FJSSP.Hence, Tabu search and Genetic Algorithm, exemplifying respectively local search and populationbased meta-heuristic approaches, are introduced for the resolution of the FJSSP.Most relevant issues related to the applicability of theses algorithms to the problem in hand are exposed; particularly coding and decoding solution schemes and algorithm operators are detailed.The chapter also proposes a discrete Harmony Search (HSA) Music-inspired Algorithm for the FJSSP.The effectiveness of the proposed approaches and operators is assessed and proved empirically, relatively to the implemented Tabu search and genetic algorithms approaches as well as to others literature results.