The proposed methodology is based on efficient clustering technique for facilitating the decision-maker in the analysis of the solutions of multi-objective problems .Choosing a solution for system implementation from the Pareto-optimal set can be a difficult task, generally because Pareto-optimal sets can be extremely large or even contain an infinite number of solutions. The proposed technique...

Many designers concede that there is typically more than one measure of performance for an artifact. Often, a large system is decomposed into smaller subsystems each having its own set of objectives, constraints, and parameters. The performance of the final design is a function of the performances of the individual subsystems. It then becomes necessary to consider the tradeoffs that occur in a ...

  In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Pareto-optima...

Many real-world optimization problems have several, usually conflicting objectives. Evolutionary multi-objective optimization usually solves this predicament by searching for the whole Pareto-optimal front of solutions, and relies on a decision maker to finally select a single solution. However, in particular if the number of objectives is large, the number of Pareto-optimal solutions may be hu...

For decision support under a multiobjective environment, it is effective to offer a Pareto optimal solution set with uniform distribution to the decision-maker. In this paper, a new optimization method for obtaining a Pareto optimal solution set with such uniform distribution is proposed. In order to overcome the difficulty of realizing this goal, the concept of cannibalism is introduced in BUG...

Abstract In this paper, a fuzzy PID with new structure is proposed to solve the load frequency control in interconnected power systems. in this study, a new structure and effective of the fuzzy PID-type Load frequency control (LFC) is proposed to solve the load frequency control in interconnected power systems. The main objective is to eliminate the deviations in the frequency of different area...

We propose a general-purpose algorithm APS (Adaptive Pareto-Sampling) for determining the set of Pareto-optimal solutions of bicriteria combinatorial optimization (CO) problems under uncertainty, where the objective functions are expectations of random variables depending on a decision from a finite feasible set. APS is iterative and population-based and combines random sampling with the soluti...

Post-Pareto Optimality Analysis to Efficiently Identify Promising Solutions for Multi-Objective Problems Heidi A. Taboada and David W. Coit Department of Industrial and Systems Engineering, Rutgers University, 96 Frelinghuysen Rd. Piscataway, NJ 08854, USA ABSTRACT: Techniques have been developed and demonstrated to efficiently identify particularly promising solutions from among a Pareto-optim...

This work presents a new learning scheme for improving generalization of Multilayer Perceptrons (MLPs). The proposed Multi-objective algorithm (MOBJ) approach minimizes both the sum of squared error and the norm of network weight vectors to obtain the Pareto-optimal solutions [1]. Preliminar results are shown in [3]. Since the Pareto-optimal solutions are not unique, we need a decision phase in...