Paper Info
Title
A Two-Phase Variable Neighborhood Search For Flexible Job Shop Scheduling Problem With Energy Consumption Constraint
Abstract
This paper investigates flexible job shop scheduling problem (FJSP) with energy consumption constraint, the goal of which is to minimize makespan and total tardiness under the constraint that total energy consumption doesn't exceed a given threshold. Energy consumption constraint is not always met and a new method for this constraint is proposed. A two-phase variable neighborhood search (TVNS) is presented. In the first phase, the problem is converted into FJSP with makespan, total tardiness and total energy consumption and a VNS is applied for the new problem. In the second phase, another VNS is for the original problem by strategies for comparing solutions and updating the non-dominated set X of the first phase. The current solution of TVNS is replaced with a member of X every a prefixed number of iterations to improve solution quality. Extensive experiments are conducted and computational results validate the effectiveness and advantages of TVNS for the considered FJSP.
Year
DOI
Venue
2018
10.1007/978-3-319-95930-6_72
INTELLIGENT COMPUTING THEORIES AND APPLICATION, PT I
Keywords
Field
DocType
Flexible job shop scheduling problem, Energy consumption constraint, Variable neighborhood search
Mathematical optimization,Tardiness,Job shop scheduling,Variable neighborhood search,Job shop scheduling problem,Computer science,Artificial intelligence,Energy consumption,Machine learning
Conference
Volume
ISSN
Citations 
10954
0302-9743
0
PageRank 
References 
Authors
0.34
12
2
Name
Order
Citations
PageRank
Chengzhi Guo100.68
De-ming Lei217618.60