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...

For Electric Vehicles (EVs), Weight and losses reduction are important factors not only in reducing the energy consumption and cost but also in increasing autonomy. This paper describes the application of an evolutionary algorithm for multiobjective optimization in the traction chain (TC) of pure EV. In this study, the optimisation algorithm is based on the Strength Pareto Evolutionary Algorith...

We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral Transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-l...

This paper presents a new approach to treat reactive power (VAr) planning problem using multi-objective evolutionary algorithms. Specifically, Strength Pareto Evolutionary Algorithm (SPEA) and Multi-Objective Particle Swarm Optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi-objective optimization probl...

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...

Local Indicators of Spatial Aggregation (LISA) can be used as objectives in a multicriteria framework when highly autocorrelated areas (hot-spots) must be identified and geographically located in complex areas. To do so, a Multi-Objective Evolutionary Algorithm (MOEA) based on SPEA2 (Strength Pareto Evolutionary Algorithm v.2) has been designed to evaluate three different fitness functions (fin...

In industries machine maintenance is used in order to avoid untimely machine fails as well as to improve production effectiveness. This research regards a permutation flow shop scheduling problem with aging and learning effects considering maintenance process. In this study, it is assumed that each machine may be subject to at most one maintenance activity during the planning horizon. The objec...

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...

This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the EED as a true multiobjective optimization problem with competing and noncommensurable obj...