Title
An asymptotically optimal algorithm for large-scale mixed job shop scheduling to minimize the makespan
Abstract
This paper considers the large-scale mixed job shop scheduling problem with general number of jobs on each route. The problem includes ordinary machines, batch machines (with bounded or unbounded capacity), parallel machines, and machines with breakdowns. The objective is to find a schedule to minimize the makespan. For the problem, we define a virtual problem and a corresponding virtual schedule, based on which our algorithm TVSA is proposed. The performance analysis of the algorithm shows the gap between the obtained solution and the optimal solution is O(1), which indicates the algorithm is asymptotically optimal.
Year
DOI
Venue
2017
10.1007/s10878-015-9974-7
J. Comb. Optim.
Keywords
Field
DocType
Job shop,Makespan,Batch machine,Flexible machine,Available constrain
Mathematical optimization,Job shop scheduling,Job shop scheduling problem,Computer science,Job shop,Flow shop scheduling,Asymptotically optimal algorithm,Bounded function
Journal
Volume
Issue
ISSN
33
2
1382-6905
Citations 
PageRank 
References 
1
0.35
13
Authors
3
Name
Order
Citations
PageRank
Manzhan Gu1364.99
Xiwen Lu218221.03
Jinwei Gu368739.49