in this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. since cell formation problem is np-hard, two algorithms based on genetic and modified particle swarm optimization (mpso) algorithms are developed to solve the problem. for generating initial solutions in these algorithms, a new heuristic method is developed, which always cre...

one of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. in this regard, there have many models developed, proposing better management in order to maintain water quality. most of these models require input parameters that are either hardly available or time-consuming and expensive to...

Abstract Multiobjective particle swarm optimization (MOPSO) algorithm faces the difficulty of prematurity and insufficient diversity due to selection inappropriate leaders inefficient evolution strategies. Therefore, circumvent rapid loss population premature convergence in MOPSO, this paper proposes a knowledge-guided multiobjective using fusion learning strategies (KGMOPSO), which an improved...

Financial health of many organizations now-a-days is being affected by investment in software and their cost estimation. Therefore, to provide effective cost estimation models are the most complex activity in software engineering fields. This paper presents a fuzzy clustering and optimization model for software cost estimation. The proposed model uses Pearson product-moment correlation coeffici...

This chapter examines the performance characteristics of both asynchronous and synchronous parallel particle swarm optimisation algorithms in heterogeneous, fault-prone environments. The chapter starts with a simple parallelisation paradigm, the Master-Slave model using Multi-Objective Particle Swarm Optimisation (MOPSO) in a heterogeneous environment. Extending the investigation to general, di...

job shop scheduling problem has significant importance in many researchingfields such as production management and programming and also combinedoptimizing. job shop scheduling problem includes two sub-problems: machineassignment and sequence operation performing. in this paper combination ofparticle swarm optimization algorithm (pso) and gravitational search algorithm(gsa) have been presented f...

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...

this paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. the model makes use of the newly introduced particle swarm optimization algorithm. a two step optimization model is developed and solved with the particle swarm optimization method. the model first carries out an exhaustive enumeration search for all feasible sets of p...

In present study, a three-step multi-objective optimization algorithm of cyclone separators is catered for the design objectives. First, the pressure drop (Dp) and collection efficiency (h) in a set of cyclone separators are numerically evaluated. Secondly, two meta models based on the evolved Group Method of Data Handling (GMDH) type neural networks are regarded to model the Dp and h as the re...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...