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...

How to conduct automated business negotiation over the Internet is an important issue for agent research. In most bilateral negotiation models, two negotiation agents negotiate by sending proposals and counterproposals back and forth. Proposals and counterproposals usually use a set of negotiation primitives to define the contents. These primitives deal with complete proposals or the whole nego...

In this paper, a procedure has been introduced to the multi-objective optimal design of semi-active tuned mass dampers (SATMDs) with variable stiffness for nonlinear structures considering soil-structure interaction under multiple earthquakes. Three bi-objective optimization problems have been defined by considering the mean of maximum inter-story drift as safety criterion of structural compone...

The Pareto dominance relation, widely used in a number of decision making areas, can suffer from a lack of discriminatory power, which may result in a large number of undominated or optimal solutions. By strengthening this relation, we can narrow down this optimal set further, which is desirable e.g., for presenting a smaller number of more interesting solutions to a decision maker. This paper ...

In this study criterion of maximum profit intensity for transportation problems, in contrast to the known criteria of minimum expenses or minimum time for transportation, is considered. This criterion synthesizes financial and time factors and has real economic sense. According to the purpose of this paper, the algorithm of the solution of such a transportation problem is constructed. It is sho...

In this paper we address the question of how many objective functions are really needed to decide whether a given point is Pareto optimal. We prove a reduction result for the case of quasi-convex objective functions and a convex feasible set. This result states that in order to decide whether a point x in the decision space is Pareto optimal it suuces to consider at most n + 1 objectives at a t...

Budget allocation problems in portfolio management are inherently multi-objective as they entail different types of assets which performance metrics not directly comparable. Existing asset methods that either consolidate multiple goals to form a single objective (a priori) or populate Pareto optimal set posteriori) may be sufficient because decision maker (DM) possess comprehensive knowledge th...

Multiobjective optimization using the conventional weighted aggregation of the objectives method is known to have several drawbacks. In this paper, multiobjective optimization using the weighted aggregation method is approached with the help of evolutionary algorithms. It is shown through a number of test functions that a Pareto front can be achieved from one single run of evolutionary optimiza...

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 ...

Two methods are presented as practical approaches to reduce the size of the Pareto optimal set of multiple-objective system reliability design problems. The first method is a pseudo-ranking scheme that helps the decision-maker select solutions that reflect his/her preferences. In the second approach we used clustering techniques used in data mining, to group the data by using the k-means algori...