We consider constraint satisfaction problems where solutions must be optimized according to multiple criteria. When the relative importance of different criteria cannot be quantified, there is no single optimal solution, but a possibly very large set of Pareto-optimal solutions. Computing this set completely is in general very costly and often infeasible in practical applications. We consider s...

This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...

Pareto efficiency is a seminal condition in the bargaining problem which leads autonomous agents to a Nash-equilibrium. This paper investigates the problem of the generating Pareto-optimal offers in bilateral multi-issues negotiation where an agent has incomplete information and the other one has perfect information. To this end, at first, the bilateral negotiation is modeled by split the pie g...

In this paper, we develop a novel algorithm which finds a subset of Pareto front of a Multi-Objective Distributed Constraint Optimization Problem. This algorithm utilizes the Lp-norm method, pseudo-tree, and Dynamic Programming technique. Furthermore, we show that this Lp-norm based algorithm can only guarantee to find a Pareto optimal solution, when we employ L1-norm (Manhattan norm).

Multi-objective problems are often solved by modifying them into equivalent single objective problems using pre-defined weights or utility functions. Then, a multi-objective problem is solved similar to a single objective problem returning a single solution. These methods can be problematic because assigning appropriate numerical values (i.e., weights) to an objective function can be challengin...

In this paper, we propose a sufficient condition for a solution to be optimal for a 2-additive Choquet integral in the context of multiobjective combinatorial optimization problems. A 2-additive Choquet optimal solution is a solution that optimizes at least one set of parameters of the 2-additive Choquet integral. We also present a method to generate 2-additive Choquet optimal solutions of mult...

The automated shape optimization of an electrostatic micromotor with radial field is tackled. Two objectives in mutual contrast i.e. static torque and torque ripple, depending on two design variables, are considered. An innovative procedure for vector optimization which aims at obtaining as many optimal solutions as possible, is presented. To this end, a non-dominated sorting genetic algorithm ...