Blending roulette wheel selection with simulated annealing for job shop scheduling problem

• Published in: Michael Faraday IET International Summit 2015 p. 100
• Main Authors: Chakraborty, S, Bhowmik, S
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2015; The Institution of Engineering & Technology
• Subjects: Algorithms; Combinatorial analysis; Combinatorial mathematics; Computer simulation; Job shop scheduling; Job shops; Optimisation; Optimisation techniques; Optimization; Other topics in statistics; Production management; Production scheduling; Simulated annealing; Statistics; Systems theory applications; Systems theory applications in industry; combinatorial mathematics; simulated annealing; simulated annealing method; JSSP; probability; sequence constraint; job shop scheduling problem; Roulette wheel selection; nonzero probability; minimum makespan; NP-complete problem class; approximation algorithm; combinatorial optimization problems; minimisation; job shop scheduling
• ISBN: 9781785611865; 1785611860
• DOI: 10.1049/cp.2015.1696

The Job Shop Scheduling Problem (known as JSSP) is a wellknown and one of the difficult combinatorial optimization problems and treated as a member of NP-complete problem class. This paper presents an algorithm based on Simulated Annealing method to solve the Job Shop Scheduling problem. It is an approximation algorithm for finding the minimum makespan in a job shop. The proposed algorithm is based on Roulette wheel selection and simulated annealing, a generalization of the well known and effective iterative improvement approach for combinatorial optimization problems. The generalization involves the acceptance of cost-increasing transitions with a nonzero probability to avoid getting stuck in local minima. The problem studied in this research focuses on the sequencing of operations and allocation of operation to the machine under some sequence constraint.