A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system

This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased perform...

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Bibliographic Details
Published in:Reliability engineering & system safety Vol. 136; pp. 62 - 74
Main Authors: Azadeh, A., Maleki Shoja, B., Ghanei, S., Sheikhalishahi, M.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.04.2015
Subjects:
Allocations
Combinatorial analysis
Cost engineering
Genetic algorithm
Genetic algorithms
Machine shops
Makespan
Optimization
Purchasing
Redundancy
Reliability
Scheduling
Series-parallel system
Simulated annealing
Series-parallel system
Makespan
Scheduling
Reliability
Redundancy
Genetic algorithm
ISSN:0951-8320, 1879-0836
Online Access:Get full text
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Summary:This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased performance and complete failure. Moreover, warm standby redundancy is considered for the redundancy allocation problem. Three objectives are considered for the problem: (1) minimizing system purchasing cost, (2) minimizing makespan, and (3) maximizing system reliability. Universal generating function is employed to evaluate system performance and overall reliability of the system. Since the problem is in the NP-hard class of combinatorial problems, genetic algorithm (GA) is used to find optimal/near optimal solutions. Different test problems are generated to evaluate the effectiveness and efficiency of proposed approach and compared to simulated annealing optimization method. The results show the proposed approach is capable of finding optimal/near optimal solution within a very reasonable time. •A redundancy-scheduling optimization problem for a multi-state series parallel system.•A flow shop with multi-state machines and warm standby redundancy.•Objectives are to optimize system purchasing cost, makespan and reliability.•Different test problems are generated and evaluated by a unique genetic algorithm.•It locates optimal/near optimal solution within a very reasonable time.
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ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2014.11.009