The objective of this paper is to develop matrix games with pay-offs of triangular hesitant fuzzy elements (THFEs). To solve such games, a new methodology has been derived based on the notion of weighted average operator and score function of THFEs. Firstly, we formulate two non-linear programming problems with THFEs. Then applying the score function of THFEs, we transform these two problems in...

In the recent decades, rapid population growth has led to the significant increase in food demand. Food supply chain has always been one of the most important and challenging management issues. Product with short age, especially foodstuffs, is the most problematic challenges for supply chain management. These challenges are mainly due to the diversity in the number of these goods, the special n...

in this paper, a multi-objective method is used to optimize a heat recovery steam generator (hrsg). two objective functions have been used in the optimization, which are irreversibility and hrsg equivalent volume. the former expresses the exergetic efficiency and the latter demonstrates the cost of the hrsg. decision variables are geometric and operational parameters of the hrsg. the results of...

this paper focuses on multi-objective designing of multi-machine thyristor controlled series compensator (tcsc) using strength pareto evolutionary algorithm (spea). the tcsc parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a spea ...

In this article, a multi objective model is presented to select and allocate the order to suppliers in uncertainty condition and in a multi source, multi customer and multiproduct case in a multi period state at two levels of supply chain. Objective functions considered in this study as the measures to evaluate suppliers are cost including purchase, transportation and ordering costs, timely del...

Abstract This paper proposes the Self-Adaptive algorithm for Multi-Objective Constrained Optimization by using Radial Basis Function Approximations, SAMO-COBRA. automatically determines best Function-fit as surrogates objectives well constraints, to find new feasible Pareto-optimal solutions. SAMO-COBRA is compared a wide set of other state-of-the-art algorithms (IC-SA-NSGA-II, SA-NSGA-II, NSGA...