Multi-objective optimization of stochastic failure-prone manufacturing system with consideration of energy consumption and job sequences

Multi-objective optimization of stochastic failure-prone manufacturing system with consideration... In this paper, multi-objective optimization of energy-aware multi-product failure-prone manufacturing system is explored. The purpose is to determine the best sequence of jobs, optimal production rate and optimum preventive maintenance time for simultaneous optimization of three criterions of total weighted quadratic earliness and tardiness, system reliability and energy-consumption cost. Considering the uncertainties of the problem such as stochastically machine breakdown and maintenance, stochastic processing times as well as NP-hard nature of the problem, it is not possible to propose an analytical solution to this problem. Therefore, two novel algorithms by combining (1) simulation and NSGA-II/PSO and (2) simulation and NSGA-II/GA are proposed for solving this problem. A set of Pareto optimal solutions was obtained via this algorithm. Results show that the both methods converge to a same optimal solution, but the rate of convergence with NSGA-II/PSO is faster than NSGA-II/GA. The algorithms are evaluated by solving small-, medium- and large-scale problems. To the best of our knowledge, multi-product failure-prone manufacturing systems by considering sequence of jobs have not been explored in any paper and for the first time a new hedging point policy is presented for the mentioned problem. Keywords Failure-prone manufacturing system · Energy consumption · Multi-objective optimization · Modified hedging http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Environmental Science and Technology Springer Journals

Multi-objective optimization of stochastic failure-prone manufacturing system with consideration of energy consumption and job sequences

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Islamic Azad University (IAU)
Subject
Environment; Environment, general; Environmental Science and Engineering; Environmental Chemistry; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution; Soil Science & Conservation; Ecotoxicology
ISSN
1735-1472
eISSN
1735-2630
D.O.I.
10.1007/s13762-018-1742-7
Publisher site
See Article on Publisher Site

Abstract

In this paper, multi-objective optimization of energy-aware multi-product failure-prone manufacturing system is explored. The purpose is to determine the best sequence of jobs, optimal production rate and optimum preventive maintenance time for simultaneous optimization of three criterions of total weighted quadratic earliness and tardiness, system reliability and energy-consumption cost. Considering the uncertainties of the problem such as stochastically machine breakdown and maintenance, stochastic processing times as well as NP-hard nature of the problem, it is not possible to propose an analytical solution to this problem. Therefore, two novel algorithms by combining (1) simulation and NSGA-II/PSO and (2) simulation and NSGA-II/GA are proposed for solving this problem. A set of Pareto optimal solutions was obtained via this algorithm. Results show that the both methods converge to a same optimal solution, but the rate of convergence with NSGA-II/PSO is faster than NSGA-II/GA. The algorithms are evaluated by solving small-, medium- and large-scale problems. To the best of our knowledge, multi-product failure-prone manufacturing systems by considering sequence of jobs have not been explored in any paper and for the first time a new hedging point policy is presented for the mentioned problem. Keywords Failure-prone manufacturing system · Energy consumption · Multi-objective optimization · Modified hedging

Journal

International Journal of Environmental Science and TechnologySpringer Journals

Published: May 28, 2018

References

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