<span>Multi-objective algorithms are used to achieve high performance for quality of service (QoS) in wireless sensor networks (WSNs) is an important field researchers because these improve two or more conflicting objectives and present the best trade-off between solve multi-objective problems (MOPs). Previous research proposed algorithm that relies on non-dominated sorting genetic 3 (NSG...

Task scheduling is a crucial issue in distributed (disbursed) heterogeneous processing environment and significantly influence the performance of the system. The task scheduling problem has been identified to be NP-complete in its universal frame. In this paper the task scheduling problem is investigated using multiple-objective particle (molecule) swarm optimization algorithm with crowded disp...

The performance of horizontal axis tidal current turbines (HATCT) strongly depends on their geometry. According to this fact, the optimum performance will be achieved by optimized geometry. In this research study, the multi objective optimization of the HATCT is carried out by using four different multi objective optimization algorithms and their performance is evaluated in combination with bla...

This article addresses a general tri-objective two-echelon capacitated vehicle routing problem (2E-CVRP) to minimize the total travel cost, customers waiting times and carbon dioxide emissions simultaneously in distributing perishable products. In distributing perishable products, customers’ satisfaction is very important and is inversely proportional to the customers waiting times. The propose...

A new model and solution for the energy minimizing vehicle routing problem with time windows (EVRPTW) and customers’ priority is presented in this paper. In this paper unlike prior attempts to minimize cost by minimizing overall traveling distance, the model also incorporates energy minimizing which meets the latest requirements of green logistics. This paper includes the vehicles load as an ad...

Abstract The flexible job-shop scheduling problem (FJSP) is a critical model in manufacturing systems that assigns operations from different jobs to various machines. However, optimizing multiple targets during the production process always necessary. While non-dominated sorting genetic algorithm (NSGA-II) an effective method solve multi-objective FJSP, it can have main drawbacks of converging ...

We apply the NSGA-II algorithm and its controlled elitist version NSGA-IIc for the intensity modulated beam radiotherapy dose optimization problem. We compare the performance of the algorithms with objectives for which deterministic optimization methods provide global optimal solutions. The number of parameters to be optimized can be up to a few thousands and the number of objectives varies fro...

This chapter presents the application of a comprehensive statistical analysis for both algorithmic performance comparison and optimal parameter estimation on a multi-objective digital signal processing problem. The problem of designing optimum digital finite impulse response (FIR) filters with the simultaneous approximation of the filter magnitude and phase is posed as a multiobjective optimiza...