A multiobjective nonlinear programming problem is considered. Sufficiency theorems are derived for efficient and properly efficient solutions under generalized (F, ρ)-convexity assumptions. Weak, strong and strict converse duality theorems are established for a general Mond–Weir type dual relating properly efficient solutions of the primal and dual problems.

In this paper, the portfolio selection problem is considered, where fuzziness and randomness appear simultaneously in optimization process. Since return and dividend play an important role in such problems, a new model is developed in a mixed environment by incorporating fuzzy random variable as multi-objective nonlinear model. Then a novel interactive approach is proposed to determine the pref...

This paper presents a multi-objective and multi-service location-allocation model with capacity planning to design a healthcare facilities network through considering a referral system. Therefore, a mixed integer nonlinear programming (MINLP) model containing two objective functions is proposed. The first objective function is  relates to minimization of total opening cost, minimization of tota...

delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. in this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several produ...

data envelopment analysis (dea) is a method to evaluate the relative efficiency of decision making units (dmus). in this method, the issue has always been to determine a set of weights for each dmu which often caused many problems. since the dea models also have the multi-objective linear programming (molp) problems nature, a rational relationship can be established between molp and dea problem...

this paper uses integrated data envelopment analysis (dea) models to rank all extreme and non-extreme efficient decision making units (dmus) and then applies integrated dea ranking method as a criterion to modify genetic algorithm (ga) for finding pareto optimal solutions of a multi objective programming (mop) problem. the researchers have used ranking method as a shortcut way to modify ga to d...

Abstract This paper addresses the problem of approximating set all solutions for Multi-objective Markov Decision Processes. We show that in vast majority interesting cases, number is exponential or even infinite. In order to overcome this difficulty we propose approximate by means a limited precision approach based on White’s multi-objective value-iteration dynamic programming algorithm. prove ...