This paper proposes a homogeneous distributed computing (HDC) framework for multi-objective evolutionary algorithm (MOEA). In this framework, multiple processors divide a work into several pieces and carry them out in parallel. Every processor does its task in a homogeneous way so that the overall procedure becomes not only faster but also fault-tolerant and independent to the number of process...

Due to limited financial resources and high costs of infrastructure projects, project stakeholders seek gain maximum profits with optimal resource utilization as well cost time minimization. Therefore, this study presents a multi-mode resource-constrained scheduling model considering the uncertain parameters together goals maximizing net present value minimizing usage fluctuation. Also, assumpt...

The aim os this paper is to study the hybridization of two multi-objective algorithms in the context of a real problem, the MANETs problem. The algorithms studied are Particle Swarm Optimization (MOPSO) and a new multiobjective algorithm based in the combination of NSGA-II with Evolution Strategies (ESN). This work analyzes the improvement produced by hybridization over the Pareto’s fronts comp...

Stock traders consider several factors or objectives in making decisions. Moreover, they differ in the importance they attach to each of these objectives. This requires a tool that can provide an optimal tradeoff among different objectives, a problem aptly solved by a multi-objective optimization (MOO) system. This paper aims to investigate the application of multi-objective optimization to end...

this paper explores the capabilities of multi-objective particle swarm optimization algorithmin a simulation-optimization model for solving waste load allocation problems. the main goals are totaltreatment costs, violation of the water quality standards and equity. in this research, the water qualitysimulation model is coupled with a multi-objective optimization model, mopso. in order to derive...

The paper presents a novel Modulated Power Filter and Compensator (MPFC) scheme for voltage stability, energy conservation, loss reduction, power factor correction, and power quality enhancement for electric distribution systems based on Multi-Objective Particle Swarm Optimisation (MOPSO). The MPFC scheme was developed by the first author to vary the shunt power filter equivalent admittance, mo...

This paper presents an algorithm for multiobjective optimization that blends together a number of heuristics. A population of agents combines heuristics that aim at exploring the search space both globally and in a neighborhood of each agent. These heuristics are complemented with a combination of a local and global archive. The novel agentbased algorithm is tested at first on a set of standard...

Efficient portfolio design is a principal challenge in modern computational finance. Optimization based on Markowitz two-objective mean-variance approach is computationally expensive for real financial world. Practical portfolio design introduces further complexity as it requires the optimization of multiple return and risk measures. Some of these measures are nonlinear and nonconvex. The probl...