This paper presents a systematic comparative study of CMEA (constraint method-based multiobjective evolutionary algorithm) with several other commonly reported mulitobjective evolutionary algorithms (MOEAs) in solving a three-objective optimization problem. The best estimate of the noninferior space was also obtained by solving this multiobjective (MO) problem using a binary linear programming ...

In the present paper, a multiobjective linear programming problem under uncertainty, particularly when parameters are given in interval forms, is investigated. this case, it assumed that objective coefficients and constraints have arrived numbers. Considering suitable order relation for numbers, solution procedure dealing with such developed. A numerical example provided to illustrate efficienc...

This paper addresses the problem of finding an approximation to the minimal element set of the objective space for the class of multiobjective deterministic finite horizon optimal control problems. The objective space is assumed to be partially ordered by a pointed convex cone containing the origin. The approximation procedure consists of a two-step discretization in time and state space. Follo...

fuzzy linear programming problem occur in many elds such as mathematical modeling, control theory and management sciences, etc. in this paper we focus on a kind of linear programming with fuzzy numbers and variables namely fully fuzzy linear programming (fflp) problem, in which the constraints are in inequality forms. then a new method is proposed to ne the fuzzy solution for solving (fflp). ...

The chapter aims to give computational algorithm to solve a multiobjective non-linear programming problem using Neutrosophic geometric programming technique. As the Neutrosophic optimization technique utilizes degrees of truth-membership, falsity-membership and indeterminacy-membership functions, we made a study of correspondence among those membership functions to see its impact on optimizatio...

In this paper, artificial neural networks for solving multiobjective optimization problems have been considered. The Tank-Hopfield model for linear programming has been extended, and then the neural model for finding Pareto-optimal solutions in the linear multi-criterion optimization problem with continuous decision variables has been discussed. Furthermore, the model for solving quasi-quadrati...

This paper shows how a formal modeling framework, Evolutionary Systems Design (ESD), for evolutionary problem definition and solution, can be used for problem adaptation and restructuring (i.e., reengineering) in optimization problems, as developed for Multiobjective Linear Programming (MOLP). R es t ructuring through a heuristic controls/goals/values referral process and adaptation are discuss...