Multi-objective programming became more and more popular in real world decision making problems in recent decades. There is an underlying and fundamental uncertainty in almost all of these problems. Among different frameworks of dealing with uncertainty, probability and statistic-based schemes are well-known. In this paper, a method is developed to find some efficient solutions of a multi-objective stochastic programming problem. The method composed a process of transforming the stochastic multi-objective problem to a bi-objective equivalent using the concept of Chebyshev inequality bounds and then solving the obtained problem with a fuzzy set based approach. Application of the proposed method is examined on two numerical examples and the results are compared with different methods. These comparisons illustrated that the results are satisfying.
Accepté le :
DOI : 10.1051/ro/2018018
Mots-clés : Multi-objective decision-making, stochastic programming, mean–variance criterion, fuzzy set based approach
@article{RO_2018__52_4-5_1201_0, author = {Amoozad Mahdiraji, Hannan and Razavi Hajiagha, Seyed Hossein and Hashemi, Shide Sadat and Zavadskas, Edmundas Kazimieras}, title = {Bi-objective mean{\textendash}variance method based on {Chebyshev} inequality bounds for multi-objective stochastic problems}, journal = {RAIRO - Operations Research - Recherche Op\'erationnelle}, pages = {1201--1217}, publisher = {EDP-Sciences}, volume = {52}, number = {4-5}, year = {2018}, doi = {10.1051/ro/2018018}, zbl = {1433.90092}, mrnumber = {3880600}, language = {en}, url = {http://www.numdam.org/articles/10.1051/ro/2018018/} }
TY - JOUR AU - Amoozad Mahdiraji, Hannan AU - Razavi Hajiagha, Seyed Hossein AU - Hashemi, Shide Sadat AU - Zavadskas, Edmundas Kazimieras TI - Bi-objective mean–variance method based on Chebyshev inequality bounds for multi-objective stochastic problems JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2018 SP - 1201 EP - 1217 VL - 52 IS - 4-5 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2018018/ DO - 10.1051/ro/2018018 LA - en ID - RO_2018__52_4-5_1201_0 ER -
%0 Journal Article %A Amoozad Mahdiraji, Hannan %A Razavi Hajiagha, Seyed Hossein %A Hashemi, Shide Sadat %A Zavadskas, Edmundas Kazimieras %T Bi-objective mean–variance method based on Chebyshev inequality bounds for multi-objective stochastic problems %J RAIRO - Operations Research - Recherche Opérationnelle %D 2018 %P 1201-1217 %V 52 %N 4-5 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2018018/ %R 10.1051/ro/2018018 %G en %F RO_2018__52_4-5_1201_0
Amoozad Mahdiraji, Hannan; Razavi Hajiagha, Seyed Hossein; Hashemi, Shide Sadat; Zavadskas, Edmundas Kazimieras. Bi-objective mean–variance method based on Chebyshev inequality bounds for multi-objective stochastic problems. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 4-5, pp. 1201-1217. doi : 10.1051/ro/2018018. http://www.numdam.org/articles/10.1051/ro/2018018/
[1] A fuzzy stochastic multi-objective optimization model to configure a supply chain considering a new product development. Appl. Math. Model. 40 (2016) 7545–7570. | DOI | MR | Zbl
, , and ,[2] A multi-objective stochastic programming approach for supply chain design considering risk. Int. J. Prod. Econ. 116 (2008) 129–138. | DOI
, , and ,[3] Stochastic goal programming: a mean–variance approach. Eur. J. Oper. Res. 131 (2001) 476–481. | DOI | MR | Zbl
,[4] Nonlinear Programming: Theory and Algorithms. John Wiley & Sons, New Jersey (2006). | DOI | MR | Zbl
, and ,[5] Solution approaches for the multi objective stochastic programming. Eur. J. Oper. Res. 216 (2012) 1–16. | DOI | MR | Zbl
,[6] Multi-objective stochastic programming for portfolio selection. Eur. J. Oper. Res. 177 (2007) 1811–1823. | DOI | Zbl
, and ,[7] Applications of Multi objective Optimization in Chemical Engineering. Department of Chemical Engineering, Indian Institute of Technology, Kanpur, India (2013).
, and ,[8] Stochastic approach versus multiobjective approach for obtaining efficient solutions in stochastic multiobjective programming problems. Eur. J. Oper. Res. 158 (2002) 633–648. | DOI | MR | Zbl
, , , ,[9] A Benchmark Study of Multi-Objective Optimization Methods. Michigan State University, Red Cedar Technology, East Lansing, Michigan (2009).
, and ,[10] Stochastic multi-objective models for network design problem. Expert Syst. Appl. 37 (2010) 1608–1619. | DOI
, , and ,[11] Quantitative Analysis: An Introduction. Gordon and Breach Science Publishers, Amsterdam (1999).
,[12] Multi Criteria Analysis. Springer, New York (1997). | MR
,[13] Multi Objective Programming and Planning. Dover Publication, New York (2004). | MR | Zbl
,[14] A stochastic approach to goal programming. Oper. Res. 16 (1968) 576–586. | DOI | Zbl
,[15] Multi Objective Optimization: History and Promise. Massachusetts Institute of Technology, Dept. of Aeronautics & Astronautics, Engineering Systems Division, Cambridge, Massachusetts (2004).
,[16] Multi-Objective Optimization Using Evolutionary Algorithms: An Introduction. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, India (2011).
,[17] Multi-objective stochastic programming to solve manpower allocation problem. Int. J. Adv. Manuf. Technol. 65 (2013) 183–196. | DOI
and ,[18] Trade-off analysis approach for interactive nonlinear multiobjective optimization. OR Spectr. 34 (2011) 803–816. | DOI | MR | Zbl
, ,[19] A First Course in Mathematical Modeling. Cengage Learning, Boston (2013).
, and ,[20] Multi-objective stochastic optimization of the suspension system of road vehicles. J. Sound Vib. 298 (2006) 1055–1072. | DOI
, and ,[21] Multiple objectives under uncertainty: an illustrative application of PROTRADE. Water Resour. Res. 15 (1979) 203–210. | DOI
, and ,[22] Stochastic multi-objective optimization: a survey on non-scalarizing methods. Ann. Oper. Res. 236 (2016) 475–499. | DOI | MR | Zbl
and ,[23] Multi-Objective Decision-Making Under Uncertainty: Fuzzy Logic Methods. NASA Technical Memorandum, Cleveland, Ohio (1995).
,[24] Fuzzy programming approach to multi-objective stochastic linear programming problems. Fuzzy Sets Syst. 88 (1997) 173–181. | DOI | MR | Zbl
, and ,[25] Multi objective programming in optimization of the interval objective function. Eur. J. Oper. Res. 48 (1990) 219–225. | DOI | Zbl
and ,[26] Pareto based multi-objective optimization of solar thermal energy storage using genetic algorithms. Trans. Can. Soc. Mech. Eng. 34 (2010) 463–475. | DOI
, , and ,[27] Nuclear fuel cycle optimization using multi-objective stochastic linear programming. Eur. J. Oper. Res. 31 (1987) 240–249. | DOI
and ,[28] Stochastic programming: an interactive multicriteria approach. Eur. J. Oper. Res. 10 (1982) 33–41. | DOI | MR | Zbl
,[29] Grey Information: Theory and Practical Applications. Springer, London (2006).
and ,[30] Portfolio selection. J. Finance 7 (1952) 77–91.
,[31] Portfolio selection problem: a review of deterministic and stochastic multiple objective programming models. Ann. Oper. Res. 267 (2018) 335–352. | DOI | MR | Zbl
and ,[32] A multiple stochastic goal programming approach for the agent portfolio selection problem. Ann. Oper. Res. 251 (2017) 179–192. | DOI | MR | Zbl
,[33] Introduction to Multiobjective Optimization: Noninteractive Approaches. Department of Mathematical Information Technology, University of Jyväskylä, Springer, Finland (2012).
,[34] ISTMO: an interval reference point-based method for stochastic multiobjective programming problems. Eur. J. Oper. Res. 197 (2009) 25–35. | DOI | MR | Zbl
and ,[35] Interest: a reference-point-based interactive procedure for stochastic multiobjective programming problems. OR Spectr. 32 (2010) 195–210. | DOI | MR | Zbl
, and ,[36] PROMISE: a DSS for multiple objective stochastic linear programming problems. Ann. Oper. Res. 51 (1994) 45–59. | DOI | Zbl
, and ,[37] Cours d’Économie Politique. Professé à l’Université de Lausanne. Vol. I, edited by . Lausanne (1896).
,[38] Multi-objective linear programming with interval coefficients. Kybernetes 42 (2013) 482–496. | DOI | MR | Zbl
, and ,[39] Fuzzy multi-objective linear programming based on compromise vikor method. Int. J. Inf. Tech. Decis. Mak. 13 (2014) 679–698. | DOI
, , and ,[40] An interactive fuzzy method for multiobjective stochastic linear programming problems through an expectation model. Eur. J. Oper. Res. 145 (2003) 665–675. | DOI | MR | Zbl
, and ,[41] Multi objective decision making under uncertainty: an example jór power systems, in Decision Making with Multiple Objective, edited by and . Springer-Verlag, Berlin (1985) 443–456. | DOI
and ,[42] Strange: an interactive method for multi-objective linear programming under uncertainty. Eur. J. Oper. Res. 26 (1986) 65–82. | DOI | MR | Zbl
, and ,[43] Convex Functions and Optimization Methods on Riemannian Manifolds. Kluwer Academic Publishers, Dordrecht (1994). | DOI | Zbl
,[44] Multi-objective stochastic linear programming with incomplete information: a general methodology, in Stochastic versus Fuzzy Approaches to Multi objective Mathematical Programming Under Uncertainty, edited by and . Kluwer Academic Publishers, Springer Netherlands (1990) 131–161. | DOI | MR | Zbl
and ,[45] PROMISE/scenarios: an interactive method for multi objective stochastic linear programming under partial uncertainty. Eur. J. Oper. Res. 155 (2004) 361–372. | DOI | MR | Zbl
and ,[46] Multicriteria Decision-Aid. John Wiley, New York (1992).
,[47] A fuzzy-robust stochastic multi objective programming approach for petroleum waste management planning. Appl. Math. Model. 34 (2010) 2778–2788. | DOI | MR | Zbl
, , , and ,Cité par Sources :