The comprehensive and systematic management of watersheds is essential for reducing the adverse environmental impacts arising from anthropogenically caused erosion and subsequent sedimentation. This paper describes a computational methodology that is designed to serve as a watershed decision support system and is capable of controlling environmental impacts of non-point source pollution resulti...

In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. The optimal VAR dispatch problem is formulated as a nonlinear constrained multiobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized simultaneously. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is...

Abstract: In this paper we consider various Marshall-Olkin distributions and develop autoregressive minification processes with stationary marginals as exponential, Weibull, uniform, Pareto, Gumbel, Lomax etc. The applications in reliability modelling and stress-strength analysis are considered.Problems of estimation of parameters is addressed. Various properties are examined. Modelling with re...

Statistical Quality Control (SQC) is a branch of Total Quality Management (TQM) that defines a quality philosophy and set the guiding principles that represent the foundation for a continuously improving organisation. Statistical Process Control (SPC) and Acceptance Sampling are the two major parts of SQC. SPC is an effective tool that aims to get and keep processes under control and ensure tha...

The project scheduling and resource allocation problems have been studied using different optimization methods. The resource leveling problem was proposed to reduce the resource fluctuation and was always studied independently resource constraint problem. For example, resource-constrained project scheduling problem (RCPSP) was proposed to optimize scheduling under resource constraints. This res...

The paper describes further developments of the interactive evolutionary design concept relating to the emergence of mutually inclusive regions of high performance design solutions. These solutions are generated from cluster-oriented genetic algorithm (COGAs) output and relate to a number of objectives introduced during the preliminary design of military airframes. The datamining of multi-objec...

This paper presents a layered encoding cascade evolutionary approach to solve a 0/1 knapsack optimization problem. A layered encoding structure is proposed and developed based on the schema theorem and the concepts of cascade correlation and multi-population evolutionary algorithms. Genetic algorithm (GA) and particle swarm optimization (PSO) are combined with the proposed layered encoding stru...

This paper addresses the problem of controlling mutation strength in multi-objective evolutionary algorithms and its implications for the convergence to the Pareto set. Adaptive parameter control is one major issue in the field of evolutionary computation, and several methods have been proposed and applied successfully for single objective optimization problems. In this study we examine whether...

Multicast routing problem in computer networks, with more than one objective to consider, like cost and delay, is usually treated as a mono-objective Optimization Problem, where the cost of the tree is minimized subject to a priori restrictions on the delays from the source to each destination. This paper presents a new multicast algorithm based on the Strength Pareto Evolutionary Algorithm (SP...