Title
An effective invasive weed optimization algorithm for scheduling semiconductor final testing problem.
Abstract
In this paper, we address a semiconductor final testing problem from the semiconductor manufacturing process. We aim to determine both the assignment of machines and the sequence of operations on all the machines so as to minimize makespan. We present a cooperative co-evolutionary invasive weed optimization (CCIWO) algorithm which iterates with two coupled colonies, one of which addresses the machine assignment problem and the other deals with the operation sequence problem. To well balance the search capability of the two colonies, we adopt independent size setting for each colony. We design the reproduction and spatial dispersal methods for both the colonies by taking advantage of the information collected during the search process and problem-specific knowledge. Extensive experiments and comparison show that the proposed CCIWO algorithm performs much better than the state-of-the-art algorithms in the literature for solving the semiconductor final testing scheduling problem with makespan criteria.
Year
DOI
Venue
2018
10.1016/j.swevo.2017.05.007
Swarm and Evolutionary Computation
Keywords
Field
DocType
Invasive weed optimization,Cooperative co-evolutionary,Semiconductor final testing scheduling,Makespan
Mathematical optimization,Job shop scheduling,Scheduling (computing),Computer science,Semiconductor device fabrication,Assignment problem,Optimization algorithm,Iterated function
Journal
Volume
ISSN
Citations 
38
2210-6502
5
PageRank 
References 
Authors
0.38
27
3
Name
Order
Citations
PageRank
Hong-yan Sang116511.18
Peiyong Duan28611.50
Junqing Li346242.69