Array syntax, existed in many languages, adds expressive power by allowing operations on and assignments to the array sections. When compiling to a uniprocessor machine, the array statement must be converted into a loop that maintains the correct semantics, by a process called scalarization. Scalarization presents a significant technical problem because an array assignment needs to be implement...

Purpose – The purpose of this paper is threefold: to make explicitly clear the range of efficient multi-objective optimization algorithms which are available with kriging; to demonstrate a previously uninvestigated algorithm on an electromagnetic design problem; and to identify algorithms particularly worthy of investigation in this field. Design/methodology/approach – The paper concentrates ex...

In this article, we carry out a combined econometric and multiobjective analysis using data from representative sample of Andalusian schools. particular, four models are estimated in which the students’ academic performance (scores math reading, percentage students reaching certain threshold both subjects, respectively) regressed against satisfaction with different aspects teaching-learning pro...

In order to approximate the set of Pareto optimal solutions, several evolutionary multi-objective optimization (EMO) algorithms transfer the multiobjective problem into several independent single-objective ones by means of scalarizing functions. The choice of the scalarizing functions’ underlying search directions, however, is typically problem-dependent and therefore difficult if no informatio...

Bellman RE, Zadeh LA . 1970. Decision-making in a fuzzy environment, Manage. Sci. , 17: 141-164. Hannan EL 1981. Linear programming with multiple fuzzy goals. Fuzzy Sets Syst. , 6: 235-248 Hansen MP 2000. Use of substitute Scalarizing Functions to guide Local Search based Heuristics: The case of MOTSP, J. Heuristics, 6: 419-431 Jaszkiewicz A 2002. Genetic Local Search for Multiple Objectives Co...

In this work, we propose a novel methodology to identify parameters of compartmental epidemiological models. It is based on solving multi-objective optimization problem that consists in fitting some the model outputs real observations. First, according available data considered epidemic, define where are variables. Then, solved by considering particular algorithm called ParWASF-GA (Parallel Wei...