Routing and scheduling in a flexible job shop by tabu search
Annals of Operations Research - Special issue on Tabu search
A fast taboo search algorithm for the job shop problem
Management Science
Computers and Operations Research
A genetic algorithm for the Flexible Job-shop Scheduling Problem
Computers and Operations Research
Multi-objective flexible job shop schedule: Design and evaluation by simulation modeling
Applied Soft Computing
Computers and Industrial Engineering
Flexible job-shop scheduling with parallel variable neighborhood search algorithm
Expert Systems with Applications: An International Journal
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
An artificial immune algorithm for the flexible job-shop scheduling problem
Future Generation Computer Systems
Discrepancy search for the flexible job shop scheduling problem
Computers and Operations Research
Parallel hybrid metaheuristics for the flexible job shop problem
Computers and Industrial Engineering
An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
An effective genetic algorithm for the flexible job-shop scheduling problem
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Solving Multiple-Objective Flexible Job Shop Problems by Evolution and Local Search
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A hybrid harmony search algorithm for the flexible job shop scheduling problem
Applied Soft Computing
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The multi-objective flexible job shop scheduling problem is solved using a novel path-relinking algorithm based on the state-of-the-art Tabu search algorithm with back-jump tracking. A routing solution is identified by problem-specific neighborhood search, and is then further refined by the Tabu search algorithm with back-jump tracking for a sequencing decision. The resultant solution is used to maintain the medium-term memory where the best solutions are stored. A path-relinking heuristics is designed to generate diverse solutions in the most promising areas. An improved version of the algorithm is then developed by incorporating an effective dimension-oriented intensification search to find solutions that are located near extreme solutions. The proposed algorithms are tested on benchmark instances and its experimental performance is compared with that of algorithms in the literature. Comparison results show that the proposed algorithms are competitive in terms of its computation performance and solution quality.