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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2015: Evolutionary Multi-Criterion Optimization pp 218–232Cite as

A Hybrid Algorithm for Stochastic Multiobjective Programming Problem

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 9018)

Abstract

The traditional approach in the solution of stochastic multiobjective programming problem involves transforming the original problem into a deterministic multiobjective programming problem. However, due to the complexity in practical application problems, the closed form of stochastic multiobjective programming problem is usually hard to obtain, and yet, there is surprisingly little literature that addresses this problem. The principal purpose of this paper is to propose a new hybrid algorithm to solve stochastic multiobjective programming problem efficiently, which is integrated with Latin Hypercube Sampling, Monte Carlo simulation, Support Vector Regression and Artificial Bee Colony algorithm. Several numerical examples are presented to illustrate the validity and performance of the hybrid algorithm. The results suggest that the proposed algorithm is very suitable for solving stochastic multiobjective programming problem.

Keywords

  • Stochastic programming
  • Multiobjective programming
  • Pareto efficient solution
  • Hybrid algorithm

This work was supported by National Natural Science Foundation under Grant No. 71171199, and Natural Science Foundation of Shaanxi Province under Grant No. 2013JM1003.

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Author information

Authors and Affiliations

  1. College of Materiel Management and Safety Engineering, Air Force Engineering University, Xi’an, 710051, China

    Zutong Wang & Jiansheng Guo

  2. College of Science, Air Force Engineering University, Xi’an, 710051, China

    Mingfa Zheng

  3. College of Information and Navigation, Air Force Engineering University, Xi’an, 710051, China

    Qifang He

Authors
  1. Zutong Wang
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  2. Jiansheng Guo
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  3. Mingfa Zheng
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  4. Qifang He
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Corresponding author

Correspondence to Zutong Wang .

Editor information

Editors and Affiliations

  1. Institute for Polymers and Composites/I3N,University of Minho, Guimaraes, Portugal

    António Gaspar-Cunha

  2. Dept. of Electrical and Computer Engg, University of Coimbra, Coimbra, Portugal

    Carlos Henggeler Antunes

  3. CINVESTAV-IPN Depto. de Computacíon, Col. San Pedro Zacatenco, México DF, Mexico

    Carlos Coello Coello

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Wang, Z., Guo, J., Zheng, M., He, Q. (2015). A Hybrid Algorithm for Stochastic Multiobjective Programming Problem. In: Gaspar-Cunha, A., Henggeler Antunes, C., Coello, C. (eds) Evolutionary Multi-Criterion Optimization. EMO 2015. Lecture Notes in Computer Science(), vol 9018. Springer, Cham. https://doi.org/10.1007/978-3-319-15934-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-15934-8_15

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