The most important issue in multi-objective optimization problems is to determine the Pareto points along the Pareto frontier. If the optimization problem involves multiple conflicting objectives, the results obtained from the Pareto-optimality will have the trade-off solutions that shaping the Pareto frontier. Each of these solutions lies at the boundary of the Pareto frontier, such that the i...

In this paper we present a new genetic algorithm (GA) using pareto partitioning method and apply this GA to solving the design problem of the robust PID controller with two degrees of freedom based on the partial model matching approach. This design problem is formulated as two objective minimax optimization problem. Therefore we need to generate a pareto optimal set that is properly distribute...

This paper deals with the estimation of the lognormal-Pareto and the lognormal-Generalized Pareto distributions, for which a general result concerning asymptotic optimality of maximum likelihood estimation cannot be proved. We develop a method based on probability weighted moments, showing that it can be applied straightforwardly to the first distribution only. In the lognormal-Generalized Pare...

Often the Pareto front of a multi-objective optimization problem grows exponentially with the problem size. In this case, it is not possible to compute the whole Pareto front efficiently and one is interested in good approximations. We consider how evolutionary algorithms can achieve such approximations by using different diversity mechanisms. We discuss some well-known approaches such as the d...

In this work, the optimization of control parameters for an active suspension system is considered. Here, two objectives – energy and comfort – play an important role. Thus, a multiobjective optimization problem is formulated which can be solved numerically with a set-oriented approach, for example. The result is the set of optimal compromises of the objectives, the so-called Pareto set. In cas...

In this article, we consider the novel approach of a seller and customer negotiating bilaterally about a two-part tariff, using autonomous software agents. An advantage of this approach is that win–win opportunities can be generated while keeping the problem of preference elicitation as simple as possible. We develop bargaining strategies that software agents can use to conduct the actual bilat...

We propose a multi-agent based utilitarian approach to model and understand information flows in social networks that lead to Pareto optimal informational exchanges. We model the individual expected utility function of the agents to reflect the net value of information received. We show how this model, adapted from a theorem by Karl Borch dealing with an actuarial Risk Exchange concept in the I...

This article proposes a novel Pareto-based multiobjective meta-heuristic algorithm named non-dominated ranking genetic algorithm (NRGA) to solve multi-facility location-allocation problem. In NRGA, a fitness value representing rank is assigned to each individual of the population. Moreover, two features ranked based roulette wheel selection including select the fronts and choose solutions from ...

We propose a strategy for approximating Pareto optimal sets based on the global analysis framework proposed by Smale (Dynamical systems, Academic Press, New York (1973) 531– 544). We speak about synthetic approach because the optimal set is natively approximated by means of a compound geometrical object, i.e., a simplicial complex, rather than by an unstructured scatter of individual optima. Th...