Paper Info
Title
Bee Colony Optimization algorithm with Big Valley landscape exploitation for Job Shop Scheduling problems
Abstract
Scheduling is a crucial activity in semiconductor manufacturing industry. Effective scheduling in its operations leads to improvement in the efficiency and utilization of its equipment. Job shop scheduling is an NP-hard problem which is closely related to some of the scheduling activities in this industry. This paper presents an improved bee colony optimization algorithm with big valley landscape exploitation as a biologically inspired approach to solve the job shop scheduling problem. Experimental results comparing our proposed algorithm with shifting bottleneck heuristic, tabu search algorithm and bee colony algorithm with neighborhood search on Taillard JSSP benchmark show that it is comparable to these approaches.
Year
DOI
Venue
2008
10.1109/WSC.2008.4736301
Austin, TX
Keywords
Field
DocType
optimisation,bee colony optimization algorithm,job shop scheduling problems,np-hard problem,semiconductor manufacturing industry,bee colony algorithm,search problems,job shop scheduling,bee colony algorithm with neighborhood search,scheduling activity,semiconductor device manufacture,proposed algorithm,big valley landscape exploitation,neighborhood search,improved bee colony optimization,tabu search algorithm,effective scheduling,jssp benchmark,job shop scheduling problem,shifting bottleneck heuristic,col,mean squared error,np hard problem,simulation
Mathematical optimization,Job shop scheduling,Computer science,Scheduling (computing),Simulation,Shifting bottleneck heuristic,Flow shop scheduling,Nurse scheduling problem,Optimization algorithm,Neighborhood search,Tabu search
Conference
ISBN
Citations 
PageRank 
978-1-4244-2708-6
15
0.79
References 
Authors
15
4
Name
Order
Citations
PageRank
Li-Pei Wong11098.32
Chi Yung Puan2321.59
Malcolm Yoke-hean Low3150.79
Chin Soon Chong431920.30