Paper Info
Title
Solving multiobjective flexible job-shop scheduling using an adaptive representation
Abstract
In this paper, we present an alternative representation for solving multiobjective Flexible Job-shop Scheduling Problems (FJSP). In FJSP, there may be a choice of machines that can perform any given operation. In order to schedule an operation, it needs to be assigned a machine first, a process known as routing. Most previous approaches to solving FJSP assigned machines to all schedules before beginning any scheduling. In our approach, Adaptive Representation (AdRep), we assign a machine to an operation just at the time it is ready to be scheduled, allowing the routing process to incorporate information from the scheduling environment. Experimental results show that although AdRep performance does not scale as well with problem size as some other approaches that are not simultaneously searching for machine assignments, it is able to find all best published solutions on a three-objective Pareto front including makespan, total workload, and maximum workload on any machine, while its simultaneous routing search opens up new possibilities for optimality of rescheduling in response to machine failure.
Year
DOI
Venue
2010
10.1145/1830483.1830615
GECCO
Keywords
Field
DocType
simultaneous routing search,adaptive representation,total workload,multiobjective flexible job-shop scheduling,scheduling environment,adrep performance,routing process,machine assignment,alternative representation,maximum workload,machine failure,representation,genetic algorithm,multiobjective optimization,pareto front,job shop scheduling
Mathematical optimization,Job shop scheduling,Fair-share scheduling,Computer science,Scheduling (computing),Flow shop scheduling,Two-level scheduling,Schedule,Rate-monotonic scheduling,Dynamic priority scheduling
Conference
Citations 
PageRank 
References 
0
0.34
16
Authors
2
Name
Order
Citations
PageRank
Prakarn Unachak110.69
Erik Goodman214515.19