Abstract: Bi-level programming, a tool for modeling decentralized decisions, consists of the objective(s) of the leader at its first level and that is of the follower at the second level. Three level programming results when second level is itself a bi-level programming. By extending this idea it is possible to define multi-level programs with any number of levels. Supply chain planning problem...

in this research, we address the application of uncertaintyprogramming to design a multi-site, multi-product, multi-period,closed-loop supply chain (clsc) network. in order to make theresults of this article more realistic, a clsc for a case study inthe iron and steel industry has been explored. the presentedsupply chain covers three objective functions: maximization ofprofit, minimization of n...

This paper presents a Taylor series approach for solving linear fractional de-centralized bi-level multi-objective decision-making (LFDBL-MODM) problems with asingle decision maker at the upper level and multiple decision makers at the lower level.In the proposed approach, the membership functions associated with each objective(s) ofthe level(s) of LFDBL-MODM are transformed by using a Taylor s...

  Bi-level programming, a tool for modeling decentralized decisions, consists of the objective(s) of the leader at its first level and that is of the follower at the second level. Three level programming results when second level is itself a bi-level programming. By extending this idea it is possible to define multi-level programs with any number of levels. Supply chain planning problems are co...

Linear bilevel programming is a decision making problem with a two-level decentralized organization. The leader is in the upper level and the follower, in the lower level. This study addresses linear bilevel multi-objective multi-follower programming (LB-MOMFP) problem, a special case of linear bilevel programming problems with one leader and multiple followers where each decision maker has sev...

Most of data in Multi-attribute decision making (MADM) problems are changeable rather than constant and stable. Therefore, sensitivity analysis after problem solving can effectively contribute to making accurate decisions. In this paper, we offer a new method for sensitivity analysis in multi-attribute decision making problems in which if the weights of one attribute changes, then we can dete...

A multi-objective optimization problem (MOP) is a simultaneous of more than one real-valued conflicting objective function subject to some constraints. Most MOP algorithms try provide set Pareto optimal solutions which are equally good in terms the functions. The can be infinite, and hence, analysis choice task or several among hard for decision maker (DM). In this paper, new scalarization appr...

environmental factors are one of the most sensitive issues that should be considered in many decisions. site selection is one of the most widely used spatial decision making problems and is influenced by many environmental factors. the purpose of site selection is to find a set of appropriate spatial alternatives for a particular application. site selection is a multi-criteria decision making p...