Routing and scheduling in a flexible job shop by tabu search
Annals of Operations Research - Special issue on Tabu search
Computers and Operations Research
A genetic algorithm for the Flexible Job-shop Scheduling Problem
Computers and Operations Research
Autonomous Agents and Multi-Agent Systems
Multi-objective flexible job shop schedule: Design and evaluation by simulation modeling
Applied Soft Computing
A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems
Computers and Operations Research
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
A survey of scheduling with deterministic machine availability constraints
Computers and Industrial Engineering
A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems
Applied Soft Computing
Discrepancy search for the flexible job shop scheduling problem
Computers and Operations Research
Chemical-reaction-inspired metaheuristic for optimization
IEEE Transactions on Evolutionary Computation
Parallel hybrid metaheuristics for the flexible job shop problem
Computers and Industrial Engineering
An effective heuristic for flexible job-shop scheduling problem with maintenance activities
Computers and Industrial Engineering
An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Solving Multiple-Objective Flexible Job Shop Problems by Evolution and Local Search
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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This paper proposes an effective discrete chemical-reaction optimization (DCRO) algorithm for solving the flexible job-shop scheduling problems with maintenance activity constraints. Three minimization objectives-the maximum completion time (makespan), the total workload of machines and the workload of the critical machine are considered simultaneously. In the proposed algorithm, each solution is represented by a chemical molecule. Four improved elementary reactions, i.e., on-wall ineffective collision, inter-molecular ineffective collision, decomposition, and synthesis, are developed. A well-designed crossover function is introduced in the inter-molecular collision, synthesis, and decomposition operators. Tabu search (TS) based local search is embedded in DCRO to perform exploitation process. In addition, the decoding mechanism considering the maintenance activity is presented. Several neighboring approaches are developed to improve the local search ability of the DCRO. The proposed algorithm is tested on sets of the well-known benchmark instances. Through the analysis of experimental results, the highly effective performance of the proposed DCRO algorithm is shown against the best performing algorithms from the literature.