Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Computers and Industrial Engineering - Special issue on computational intelligence for industrial engineering
Quality Engineering Using Robust Design
Quality Engineering Using Robust Design
Computers and Industrial Engineering
Local Search Genetic Algorithms for the Job Shop Scheduling Problem
Applied Intelligence
A simulated annealing algorithm for manufacturing cell formation problems
Expert Systems with Applications: An International Journal
An effective two-stage simulated annealing algorithm for the minimum linear arrangement problem
Computers and Operations Research
Robotics and Computer-Integrated Manufacturing
Expert Systems with Applications: An International Journal
A variable neighborhood search for job shop scheduling with set-up times to minimize makespan
Future Generation Computer Systems
Expert Systems with Applications: An International Journal
The periodicity and robustness in a single-track train scheduling problem
Applied Soft Computing
Minimizing the total completion time in a distributed two stage assembly system with setup times
Computers and Operations Research
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This paper investigates scheduling job shop problems with sequence-dependent setup times under minimization of makespan. We develop an effective metaheuristic, simulated annealing with novel operators, to potentially solve the problem. Simulated annealing is a well-recognized algorithm and historically classified as a local-search-based metaheuristic. The performance of simulated annealing critically depends on its operators and parameters, in particular, its neighborhood search structure. In this paper, we propose an effective neighborhood search structure based on insertion neighborhoods as well as analyzing the behavior of simulated annealing with different types of operators and parameters by the means of Taguchi method. An experiment based on Taillard benchmark is conducted to evaluate the proposed algorithm against some effective algorithms existing in the literature. The results show that the proposed algorithm outperforms the other algorithms.