Many decision making problems can be formulated as multi-objective optimization problems (MOP). There hardly exists the solution that optimizes all objective functions in MOP, and then the concept of Pareto optimal solution (or efficient solution) is introduced. Usually, there exist a lot of Pareto optimal solutions, which are considered as candidates of final decision making solution. It is an...

Abstract: In multi-objective optimization problems, the optimization target is to obtain a set of non-dominated solutions. Comparing solution sets is crucial in evaluating the performances of different optimization algorithms. The use of performance indicators is common in comparing those sets and, subsequently, optimization algorithms. A good solution set must be close to the Pareto-optimal fr...

Design of control systems is characterised by many targets, therefore the methods enabling optimisation of several objectives have received more and more attention over the past years. When dealing with multi-objective optimisation problems the notion of the scalar function optimality was extended. The most common approach was originally proposed in 19th century by Edgeworth and later generalis...

The coupling of performance functions due to common design variables and uncertainties in an engineering design process will result in difficulties in optimization design problems, such as poor collaboration among design objectives and poor resolution of design conflicts. To handle these problems, a fuzzy interactive multi-objective optimization model is developed based on Pareto solutions, whe...

In this paper, we present an automated multi-agent multi-issue negotiation solution to solve a resource allocation problem. We use a multilateral negotiation model, by which three agents bid sequentially in consecutive rounds till some deadline. Two issues are bundled and negotiated concurrently, so winwin opportunities can be generated as trade-offs exist between issues. We develop negotiation...

Proposal in this paper is a method of interpolating the pareto optimal solution in Multiobjective Genetic Algorithms. In this method, some vacancies are maked up by resuming computation of Multiobjective Genetic Algorithms. A beginning field is set up by variables of both sides of the vacancy. Then, computation of Multiobjective Genetic Algorithms is started from the beginning field again. Visu...

In this paper, we consider multiobjective two-person zero-sum games with vector payoffs and vector fuzzy payoffs. We translate such games into the corresponding multiobjective programming problems and introduce the pessimistic Pareto optimal solution concept by assuming that a player supposes the opponent adopts the most disadvantage strategy for the self. It is shown that any pessimistic Paret...

In this paper attention has been paid to the study of multiobjective linear fractional programming problem (MOLFPP) by using fuzzy set theoretic approach. In this approach, MOLFPP is transformed into multiobjective linear programming problem (MOLPP) by suitable transformation. In algorithm-I, MOLFPP is transformed into MOLPP by using fuzzy set theory and the pareto optimal solution of the trans...