Context: In requirements engineering phase of the software development life cycle, one of the main concerns of software engineers is to select a set of software requirements for implementation in the next release of the software from many requirements proposed by the customers, while balancing budget and customer satisfaction. Objective: To analyse the efficacy of Quantum-inspired Elitist Multi...

We apply the NSGA-II algorithm and its controlled elitist version NSGA-IIc for the intensity modulated beam radiotherapy dose optimization problem. We compare the performance of the algorithms with objectives for which deterministic optimization methods provide global optimal solutions. The number of parameters to be optimized can be up to a few thousands and the number of objectives varies fro...

This paper proposes a hybrid particle swarm approach called Simple Multi-Objective Particle Swarm Optimizer (SMOPSO) which incorporates Pareto dominance, an elitist policy, and two techniques to maintain diversity: a mutation operator and a grid which is used as a geographical location over objective function space. In order to validate our approach we use three well-known test functions propos...

This paper describes a genetic planning system, i.e., a program capable of solving planning problems using evolutionary techniques. As opposed to other approaches in Genetic Planning, we use a variable length chromosomes model in addition to a complex fitness function and several enhancements of the Simple Genetic Algorithm (Holland 1975), such as multipopulations, population reset, weak memeti...

In this paper, we consider a fitness-level model of a non-elitist mutation-only evolutionary algorithm (EA) with tournament selection. The model provides upper and lower bounds for the expected proportion of the individuals with fitness above given thresholds. In the case of so-called monotone mutation, the obtained bounds imply that increasing the tournament size improves the EA performance. A...

The paper addresses the optimal design of parallel manipulators based on multi-objective optimization. The objective functions used are: Global Conditioning Index (GCI), Global Payload Index (GPI), and Global Gradient Index (GGI). These indices are evaluated over a required workspace which is contained in the complete workspace of the parallel manipulator. The objective functions are optimized ...

A heuristic technique that combines a genetic algorithm with a Tabu Search algorithm is applied to the Quadratic Assignment Problem (QAP). The hybrid algorithm improves the results obtained through the application of each of these algorithms separately. The QAP is a NP-hard problem and instances of size n > 15 are still considered intractable. The results of our experiments suggest that CHC com...

We discuss the use of normal distribution theory as a tool to model the convergence characteristics of di erent GA selection schemes The models predict the proportion of optimal alleles in function of the number of generations when optimizing the bit counting function The selection schemes analyzed are proportionate selection tournament selec tion truncation selection and elitist recombination ...

Highlights: In the last 20 years, many useful t-way strategies (where t indicates the interaction strength) have been developed to help generate test suite for detecting fault due to interaction of inputs. Although useful, existing t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive system, such an assumption is invalid. This paper presents...

Today, evidence-based medicine (EBM) is proposed as the “natural” way of thinking and practicing medicine. Although it has been questioned with several arguments (little humanist, elitist, disdainful of experience, functional to the health commerce, etc.), criticism has not moved its structure. EBM was born at the beginning of the nineties; it is undoubtedly the dominant thought in today’s medi...