This paper presents the strategy for multi-criteria optimization of a prototype. There are taken into account two different optimization criteria. An original computer program was made to make possible the graphic display of regions on the 3D model surface, which exceed a limit for surface roughness, initial established. The computer program allows the automate calculation of optimal position f...

in this paper an approach based on evolutionary algorithms to find pareto optimal pair of state and control for multi-objective optimal control problems (moocp)'s is introduced‎. ‎in this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

In this paper, a fuzzy multi-objective constrained optimization problem (FMCOP) is converted to a single-objective constrained optimization problem with equality and inequality constraints (SCOP) by using α−level set of the fuzzy vector and weighting approach. A trust-region algorithm for solving problem (SCOP) is introduced to obtain α−pareto optimal solutions of problem (FMCOP). An εα−stabili...

Incorporating secondary structure information into the alignment process improves the quality of RNA sequence alignments. Instead of using fixed weighting parameters, sequence and structure components can be treated as different objectives and optimized simultaneously. The result is not a single, but a Pareto-set of equally optimal solutions, which all represent different possible weighting par...

Multi-objective problems are a category of optimization problem that contains more than one objective function and these objective functions must be optimized simultaneously. Should the objective functions be conflicting, then a set of solutions instead of a single solution is required. This set is known as Pareto optimal. Multi-objective optimization problems arise in many real world applicati...

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 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...

 Evolutionary multi-objective optimization (EMOO) finds a set of Pareto solutions rather than any single aggregated optimal solution for a multi-objective problem. The purpose of this paper is to describe a newly developed evolutionary approach --Paretobased multi-objective differential evolution (MODE). In this paper, the concept of differential evolution, which is well-known in the continuou...

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...