Swarm-based neighbourhood search for fuzzy job shop scheduling

Abstract

In this paper, fuzzy job shop scheduling problems are considered and an efficient swarm-based neighbourhood search (SNS) is proposed, in which an ordered operation-based representation and the decoding procedure are given. It is proved that most of possible actual completion times lie in the cut of fuzzy completion time for each job. In SNS, adaptive swap operation and binary tournament selection are applied to update swarm. SNS is compared with some methods from literature and computational results demonstrate that SNS has promising advantage on fuzzy scheduling.