Abstract In order to further reduce the carbon emission of manufacturing process in flexible job shop, a multi-objective integrated optimization model job-shop scheduling (FJSP) is proposed. A mathematics built this paper minimize makespan, total workload machines and emissions optimize method each machine characteristic, sequence allocation. Considering many parameters are interactional be opt...

Considering the standard particle swarm optimization (PSO) has the shortcomings of low convergence precision in job shop scheduling problems, the job shop scheduling solution is presented based on improved particle swarm optimization (A-PSO). In this paper, the basic theory of A-PSO is described. Also, the coding and the selection of parameters as well as the decoding of A-PSO are studied. It u...

This paper proposes a novel genetic algorithm (GA) approach that utilizes multichromosome to solve the flexible job-shop scheduling problem (FJSP), which involves two kinds of decisions: machine selection and operation sequencing. Typically, former is represented by string categorical values, whereas latter forms sequence operations. Consequently, chromosome conventional GAs for solving FJSP co...

The job shop scheduling problem (JSSP) has attracted much attention in the field of both information sciences and operations research. This paper considers the permutation Job shop scheduling problem with the objective of minimizing make span. Artificial Bee Colony algorithm (ABC) is one of the search heuristics used to solve global optimization problems in complex search spaces. It is observed...