One of the most comprehensive theories stochastic models is queueing theory. Through innovative analytical research with broad applicability, advanced theoretical are being developed. In present research, we would like to investigate at a queuing network model low and high priority users different server transition probabilities. The two service channels used in this study, <img src=image/13428...

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...

This research addresses the mixed-model assembly line (MMAL) by considering various constraints. In MMALs, several types of products which their similarity is so high are made on an assembly line. As a consequence, it is possible to assemble and make several types of products simultaneously without spending any additional time. The proposed multi-objective model considers the balancing and sequ...

This study proposes twooptimizationmathematicalmodels for the clustering and selection of suppliers. Model 1 performs an analysis of supplier clusters, according to customer demand attributes, including production cost, product quality and production time. Model 2 uses the supplier cluster obtained in Model 1 to determine the appropriate supplier combinations. The study additionally proposes a ...

in this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. although optimization of bi-objective problems with due dates is an essential feature of real projects, little effort has been made in studying the p-mmrcpsp while due dates are included i...

A novel multi-objective evolutionary algorithm (MOEA) is developed based on Imperialist Competitive Algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The n...

Hubs act as intermediate points for the transfer of materials in transportation system. In this study, a novel p-mobile hub location–allocation problem is developed. Hub facilities can be transferred to other hubs next period. Implementation mobile reduce costs opening and closing hubs, particularly an environment with rapidly changing demands. On hand, movement reduces lifespan adds relevant c...

A major difficulty in the use of metaheuristics (i.e. evolutionary and particle swarm algorithms) to deal with multi-objective optimization problems is the choice of a convenient point at which to stop computation. Indeed, it is difficult to find the best compromise between the stopping criterion and the algorithm performance. This paper addresses this issue using the Non-dominated Sorting Gene...

This work addresses the research and development (R&D) of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this work focus is AIDA-CMK, by enhancing AIDA-C with a new multi-objective multi-constraint optimization kernel. AIDA-C is the circuit optimizer component of AIDA, an electronic design automation framework fully developed in-house. The prop...

A Manufacture Support System using Taguchi Methods was developed and evaluated. This system consists of a Taguchi methods part, a CAE simulation part and a management part of productivity. The Taguchi methods part was firstly used for calculating the average and the standard deviation regarding all combinations using all parameters. The CAE part was then used for shortening the total time of ev...