The paper is devoted to upper bounds on the expected first hitting time of the sets of optimal solutions for non-elitist genetic algorithms with very high selection pressure. The results of this paper extend the range of situations where the upper bounds on the expected runtime are known for genetic algorithms and apply, in particular, to the Canonical Genetic Algorithm. The obtained bounds do ...

"demographic time-bomb", and Project 2000, the authors provocatively conclude that even in the next century the handywomen/supportworker will still provide care,-"No elitist programme of nursing has yet been allowed to succeed. Would an alternative based on open entry and continuing opportunity have more prospects of serving both the occupation and its public?" Currently this must be the best s...

We present an evolutionary tool to solve free-route Air Traac Flow Management problems within a three-dimensional air space 5]. This is the rst evolutionary tool which solves free-route planning problems involving a few hundred aircraft. We observe that the importance of the recombination operator increases as we scale to larger problem instances. The evolutionary algorithm is based on a varian...

This paper presents an optimal kinematic design of a 3PRC (prismatic-revolute-cylindrical) spatial translational parallel manipulator with inclined actuator arrangement by formulating a multi-objective optimization problem. Three performance criteria’s namely Global Conditioning Index (GCI), Global stiffness Index (GSI) and Workspace volume are considered as the objective functions. A multi-obj...

Abstract. Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algor...

An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper. In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search. During the iterative optimization process of EB-QPS...

This study presents a methodology for quantifying the tradeoffs between sampling costs and local concentration estimation errors in an existing groundwater monitoring network. The method utilizes historical data at a single snapshot in time to identify potential spatial redundancies within a monitoring network. Spatially redundant points are defined to be monitoring locations that do not apprec...

The fruit fly optimization algorithm (FOA) is a global optimization algorithm inspired by the foraging behavior of a fruit fly swarm. In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. A food source generating method based on a stochastic fractal with an adaptive parameter updating strategy is introduced to improve...

It is imperative to provide service consumers with facilities for selecting required web services according to their Quality of Service (QoS). Several heuristics, which are local adaptation preemptive strategy, elitist perturbation guiding strategy and global tournament strategy for directed local fine-tuning, and a hybrid clonal selection algorithm (CSPLPT) are proposed for QoS-aware web servi...