Paper Info
Title
Multi-Objective Flexible Job Shop Scheduling Problem With Energy Consumption Constraint Using Imperialist Competitive Algorithm
Abstract
In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) with energy consumption constraint is investigated and a novel imperialist competitive algorithm (ICA) is used to optimize makespan and total tardiness under a constraint that total energy consumption doesn't exceed a given threshold. The flow of ICA consists of two parts. In the first part, a MOFJSP is obtained by adding total energy consumption as objective and optimized, all generated feasible solutions are stored and updated to build a population of the second part; in the second part, the original MOFJSP is solved by starting with the population. New strategies are applied to build initial empires twice to adapt to the two-part structure and imperialist's reinforced search is added. The computational results show that the new approach to constraint is effective and ICA is a very competitive algorithm.
Year
DOI
Venue
2018
10.1007/978-3-319-95930-6_66
INTELLIGENT COMPUTING THEORIES AND APPLICATION, PT I
Keywords
Field
DocType
Flexible job shop scheduling, Energy consumption constraint, Imperialist competitive algorithm
Population,Mathematical optimization,Tardiness,Job shop scheduling,Computer science,Job shop scheduling problem,Competitive algorithm,Artificial intelligence,Energy consumption,Imperialist competitive algorithm,Machine learning
Conference
Volume
ISSN
Citations 
10954
0302-9743
0
PageRank 
References 
Authors
0.34
15
2
Name
Order
Citations
PageRank
Chengzhi Guo100.68
De-ming Lei217618.60