An effective neighborhood search algorithm for scheduling a flow shop of batch processing machines

Authors:
Deming Lei;Tao Wang
Affiliations:
School of Automation, Wuhan University of Technology, China;School of Automation, Wuhan University of Technology, China
Venue:
Computers and Industrial Engineering
Year:
2011

Citing 4
Cited 2

Fuzzy scheduling of job orders in a two-stage flowshop with batch-processing machines

International Journal of Approximate Reasoning
Minimizing makespan in a flow shop with two batch-processing machines using simulated annealing

Robotics and Computer-Integrated Manufacturing
Tabu search heuristic for two-machine flowshop with batch processing machines

Computers and Industrial Engineering
Mixed integer formulation to minimize makespan in a flow shop with batch processing machines

Mathematical and Computer Modelling: An International Journal

An improved hybrid Cuckoo Search (IHCS) metaheuristics algorithm for permutation flow shop scheduling problems

International Journal of Bio-Inspired Computation
Tabu search and lower bounds for a combined production-transportation problem

Computers and Operations Research

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Abstract

This paper considers scheduling problem of flow shop with many batch processing machines and objective of maximum lateness. An effective neighborhood search algorithm (NSA) is proposed for the problem, in which a job permutation and a batch permutation are used to indicate the solution of two sub-problems, respectively. Each job permutation consists of several family-permutations for the representation of jobs from the same family. Two swaps are applied to two permutations to produce new solutions. NSA is applied to a number of instances and compared with some methods, and computational results validate the good performance of NSA.