The shifting bottleneck procedure for job shop scheduling
Management Science
Job shop scheduling by simulated annealing
Operations Research
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation
Computers and Industrial Engineering
A fast taboo search algorithm for the job shop problem
Management Science
Guided Local Search with Shifting Bottleneck for Job Shop Scheduling
Management Science
Computers and Industrial Engineering - Special issue on computational intelligence for industrial engineering
Multiobjective Scheduling by Genetic Algorithms
Multiobjective Scheduling by Genetic Algorithms
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Genetic Algorithms
Journal of Global Optimization
A Parallel Implementation of a Job Shop Scheduling Heuristic
PARA '00 Proceedings of the 5th International Workshop on Applied Parallel Computing, New Paradigms for HPC in Industry and Academia
Lamarckian Evolution, The Baldwin Effect and Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Parallel GRASP with path-relinking for job shop scheduling
Parallel Computing - Special issue: Parallel computing in numerical optimization
An Advanced Tabu Search Algorithm for the Job Shop Problem
Journal of Scheduling
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
A very fast TS/SA algorithm for the job shop scheduling problem
Computers and Operations Research
Ant colony optimization combined with taboo search for the job shop scheduling problem
Computers and Operations Research
Geometric differential evolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Computers and Industrial Engineering
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
On the application of graph colouring techniques in round-robin sports scheduling
Computers and Operations Research
Opposition-Based Differential Evolution
IEEE Transactions on Evolutionary Computation
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The Job-Shop Scheduling Problem (JSSP) has drawn considerable interest during the last decades, mainly because of its combinatorial characteristics, which make it very difficult to solve. The good performances attained by local search procedures, and especially Nowicki and Smutnicki's i-TSAB algorithm, encouraged researchers to combine such local search engines with global methods. Differential Evolution (DE) is an Evolutionary Algorithm that has been found to be particularly efficient for continuous optimization, but which does not usually perform well when applied to permutation problems. We introduce in this paper the idea of hybridizing DE with Tabu Search (TS) in order to solve the JSSP. A competitive neighborhood is included within the TS with the aim of determining if DE is able to replace the re-start features that constitute the main strengths of i-TSAB (i.e., a long-term memory and a path-relinking procedure). The computational experiments reported for more than 100 JSSP instances show that the proposed hybrid DE-TS algorithm is competitive with respect to other state-of-the-art techniques, although, there is still room for improvement if the adequacy between the solution representation modes within DE and TS is properly stressed.