Scheduling tasks is one of the core steps to effectively exploit the capabilities of distributed or parallel computing systems. In general, scheduling is an NP-hard problem. Most existing approaches for scheduling deal with a single objective only. This paper presents a multi-objective scheduling algorithm based on particle swarm optimization (PSO). In this paper a non-dominated sorting particl...

55 Multi-Objective Optimization of Squeeze Casting Process using Evolutionary Algorithms Manjunath Patel G C, Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India Prasad Krishna, Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India Mahesh B. Parappagoudar, Department of Mechanical Engineering, Chhatrapat...

In this paper, we proposed a multi-objective Pareto based particle swarm optimization (MOPPSO) to minimize the architectural complexity and maximize the classification accuracy of a polynomial neural network (PNN). To support this, we provide an extensive review of the literature on multi-objective particle swarm optimization and PNN. Classification using PNN can be considered as a multi-object...

The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit currently available resources. One these is ensuring that reliable and near-optimum designs distribution systems (WDSs) are achieved. Designing WDSs a discrete combinatorial NP-hard optimization problem, its complexity increases when more objectives added. Among many exist...