In this paper we propose an approach to solve multi-objective structural design problem using basic t-norm based fuzzy optimization programming technique. Here a planer truss structural model in fuzzy environment has been developed. In this structural model formulation, the objective functions are the weight of the truss and the vertical deflection of loaded joint; the design variables are the ...

Designing a logistic network is a strategic and critical problem that provides an optimal platform for the effective and efficient supply chain management. In this research, we address the application of fuzzy sets to design a multi-product, multi-period, closed-loop supply chain network. The presented supply chain includes three objective functions: maximization of profit, minimization of deli...

this paper proposes per unit coding for combined economic emission load dispatch problem. in the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. in the proposed per unit coding, each function is transformed into per unit form based on its own maximum value and has a value from 0 to 1. in this paper, particle sw...

This work introduces an approach for taking into account the uncertainty of pipe friction coefficients and nodal demands in the hydraulic analysis of water supply networks. For this purpose, uncertainties are represented by fuzzy numbers and incorporated into the network's governing equations. Input uncertainties are spread out on the network and influence its hydraulic responses, including pip...

Worldwide competition originated the development of Integrated E-Supply Chains (IESC) that are distributed manufacturing systems integrating international logistics and information technologies with production. This work builds upon an IESC network design methodology previously proposed to select partners in the different IESC stages and the links connecting them. In order to rank the Pareto op...

System reliability optimization is often faced with imprecise and conflicting goals such as reducing the cost of the system and improving the reliability of the system. The decision making process becomes fuzzy and multi-objective. In this paper, we formulate the problem as a fuzzy multi-objective nonlinear program (FMOOP). A fuzzy multiobjective genetic algorithm approach (FMGA) is proposed fo...

Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty.In this paper, we focus on multi-objective linear programmingproblems in which the coefficients of constraints and the righthand side vector are fuzzy random variables. There are several methodsin the literature that convert this problem to a stochastic or<b...

The normative approach for decision-making is the dominant paradigm in designing intelligent decision agents. We discuss here the advantages of a more flexible way based on fuzzy logic. However, most exploitation methods of fuzzy preference relations do not provide good prescriptions. Recently some approaches based on the idea of reducing inconsistencies using evolutionary multiobjective optimi...

The multi-attribute group decision making (MAGDM) problem has received considerable attention in the decision analysis field and fruitful achievements have been reported in the literature. This paper focuses on the MAGDM in which the subjective absolute judgement on alternatives with respect to evaluating attributes are represented by fuzzy numbers. This paper employs the consensus degree to me...

Based on Game Theory and Multi-objective optimization problems (MOP), Game Optimization Theory (GOT) is discussed in this paper. Optimization Stability Analysis (OSA), Distance Entropy Multi-Objective Particle Swarm Optimization (DEMPSO) and Fuzzy Multi-weights Decision-making Method (FMW) are proposed as well. Game Optimization Theory, which is a comprehensive system, could not only handle mul...