A Proton Exchange Membrane Fuel Cell (PEMFC) provides stable, emission-free, high-efficiency power. Water management and durability of PEMFCs are directly affected by transport phenomena at the cathode side. In present study, investigated optimized in a tapered parallel flow field. Main channels field tapered, which increases limiting current density 41%. Two objectives, i.e. water saturation r...

Abstract This paper investigates the performance of four multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm II (NSGA-II), particle swarm (MOPSO), strength Pareto evolutionary (SPEA2), and multi-verse (MVO), in developing an optimal reinforced concrete cantilever (RCC) retaining wall. The wall design was based on two major requirements: geotechnical stability...

This paper presents a multi-objective resource-constrained project scheduling problem with positive and negative cash flows. The net present value (NPV) maximization and making span minimization are this study objectives. And since this problem is considered as complex optimization in NP-Hard context, we present a mathematical model for the given problem and solve three evolutionary algorithms;...

One of the most important aspects affecting the performance of a supply chain is the management of inventories. Managing inventory in complex supply chains is typically difficult, and may have a significant impact on the customer service level and system-wide costs. The main challenge of inventory management is that almost every inventory problem involves multiple and conflicting objectives tha...

Optimization algorithms play a critical role in electromagnetic device designs due to the ever-increasing technological and economical competition. Although evolutionary algorithm-based methods have successfully been applied different design problems, these exhibit deficiencies when solving complex problems with multimodal discontinuous objective functions, which is quite common optimization de...

This paper proposes an adaptive evolutionary radial basis function (RBF) network algorithm to evolve accuracy and connections (centers and weights) of RBF networks simultaneously. The problem of hybrid learning of RBF network is discussed with the multi-objective optimization methods to improve classification accuracy for medical disease diagnosis. In this paper, we introduce a time variant mul...

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...

In this paper, a bi-objective multi-product (r,Q) inventory model in which the inventory level is reviewed continuously is proposed. The aim of this work is to find the optimal value for both order quantity and reorder point through minimizing the total cost and maximizing the service level of the proposed model simultaneously. It is assumed that shortage could occur and unsatisfied demand coul...

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...