Current position: Home >> Scientific Research >> Paper Publications

Research on m-machine flow shop scheduling with truncated learning effects

Release Time:2019-03-13  Hits:

Indexed by: Journal Article

Date of Publication: 2019-05-01

Journal: INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

Included Journals: Scopus、SSCI、SCIE

Volume: 26

Issue: 3

Page Number: 1135-1151

ISSN: 0969-6016

Key Words: scheduling; branch-and-bound algorithm; heuristic algorithm; learning effect; flow shop

Abstract: The permutation flow shop problems with truncated exponential sum of logarithm processing times based and position-based learning effects are considered in this study. The objective is to minimize makespan and total weighted completion time, respectively. Several heuristics and a branch-and-bound algorithm are proposed in this paper. The tight worst-case bounds of some simple heuristics are also given. Numerical experiments are tested to evaluate the performance of the heuristics and branch-and-bound algorithm.

Prev One:Understanding Solvers' Continuance Intention in Crowdsourcing Contest Platform: An Extension of Expectation-Confirmation Model

Next One:A combinatorial auction mechanism for surgical scheduling considering surgeon's private availability information