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 ...

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...

Although many papers deal with the permutation flowshop scheduling problem with or without setups, according to our knowledge, little has been published tackling multi-objective optimization in presence of sequence dependent setup times. Hence, in this work we cope with this problem considering two pairs of well known independent objectives, the Cmax−TWT (Makespan-Total Weighted Tardiness ) and...

This paper focuses on a multi-objective derivation of branch-and-bound procedures. Such a procedure aims to provide the set of Pareto optimal solutions of a multi-objective combinatorial optimization problem. Unlike previous works on this issue, the bounding is performed here via a set of points rather than a single ideal point. The main idea is that a node in the search tree can be discarded i...

This paper presents a Pareto-based bi-objective optimization of hazardous materials vehicle routing and scheduling problem with time windows and shows its application to a realistic hazardous material logistics instance. A meta-heuristic solution algorithm is also proposed, which returns a set of routing solutions that approximate the frontier of the Pareto optimal solutions based on total sche...

Robustness of optimal solutions when solving network design problems is of great importance because of uncertainty in future demand. In this research the optimization of infrastructure planning in a multimodal passenger transportation network is defined as a multiobjective network design problem, with accessibility, use of urban space by parking, operating deficit and climate impact as objectiv...

This paper deals with three particular models of the bi-criteria {0,1}-knapsack problem: equal weighted items, constant sum of the criteria coe¢cients, and the combination of the two previous models. The con...guration of the Pareto frontier is presented and studied. Several properties on the number and the composition of the e¢cient solutions are devised. The connectedness of the e¢cient solut...

In this paper, we propose near admissible multiobjective search algorithms to approximate, with performance guarantee, the set of Pareto optimal solution paths in a state space graph. Approximation of Pareto optimality relies on the use of an epsilon-dominance relation between vectors, significantly narrowing the set of nondominated solutions. We establish correctness of the proposed algorithms...

This paper investigates three disparate design cases where the newly developed s-Pareto frontier based concept selection paradigm is used to compare competing design concepts under a multiobjective optimization framework. The new paradigm, which was recently introduced by the authors, is based on the principle of Pareto optimality – a principle that defines an important class of optimal solutio...

In this chapter, we present a new method for interactive multiobjective optimization, which is based on application of a logical preference model built using the Dominance-based Rough Set Approach (DRSA). The method is composed of two main stages that alternate in an interactive procedure. In the first stage, a sample of solutions from the Pareto optimal set (or from its approximation) is gener...