M. Mohammadi, R. Tavakkoli-Moghaddam, A. Ghodratnama , H. Rostami ,
Volume 22, Issue 3 (9-2011)
Abstract
Hub covering location problem, Network design, Single machine scheduling, Genetic algorithm, Shuffled frog leaping algorithm |
Hub location problems (HLP) are synthetic optimization problems that appears in telecommunication and transportation networks where nodes send and receive commodities (i.e., data transmissions, passengers transportation, express packages, postal deliveries, etc.) through special facilities or transshipment points called hubs. In this paper, we consider a central mine and a number of hubs (e.g., factories) connected to a number of nodes (e.g., shops or customers) in a network. First, the hub network is designed, then, a raw materials transportation from a central mine to the hubs (i.e., factories) is scheduled. In this case, we consider only one transportation system regarded as single machine scheduling. Furthermore, we use this hub network to solve the scheduling model. In this paper, we consider the capacitated single allocation hub covering location problem (CSAHCLP) and then present the mixed-integer programming (MIP) model. Due to the computational complexity of the resulted models, we also propose two improved meta-heuristic algorithms, namely a genetic algorithm and a shuffled frog leaping algorithm in order to find a near-optimal solution of the given problem. The performance of the solutions found by the foregoing proposed algorithms is compared with exact solutions of the mathematical programming model .
Mostafa Shirinfar, Hassan Haleh,
Volume 22, Issue 4 (12-2011)
Abstract
In this study, an outsourcer evaluation and management system is developed for a manufacturing company by use of Fuzzy goal programming (FGP). A first phase of the methodology evaluation criteria for outsources and the objectives of the company are determined. Considering the fuzziness in the decision data, linguistic variables that can be expressed in generalized fuzzy number are used. The propose approach is utilized from fuzzy sets, Analytic Network Process (ANP), fuzzy TOPSIS and Preference Ranking Organization method for enrichment evaluations (PROMETHEE) approaches. Evaluation criteria for this problem are weighted by Fuzzy ANP approach then in the Fuzzy TOPSIS and Fuzzy PROMETHEE approaches. At the second phase the FGP model developed selects the most appropriate outsourcers suitable to be strategic partners with the company and simultaneously allocates the quantities to be ordered to them. At the end, gives the computational results .
, ,
Volume 23, Issue 2 (6-2012)
Abstract
The Network Design Problem (NDP) is one of the important problems in combinatorial optimization. Among the network design problems, the Multicommodity Capacitated Network Design (MCND) problem has numerous applications in transportation, logistics, telecommunication, and production systems. The MCND problems with splittable flow variables are NP-hard, which means they require exponential time to be solved in optimality. With binary flow variables or unsplittable MCND, the complexity of the problem is increased significantly. With growing complexity and scale of real world capacitated network design applications, metaheuristics must be developed to solve these problems. This paper presents a simulated annealing approach with innovative representation and neighborhood structure for unsplittable MCND problem. The parameters of the proposed algorithms are tuned using Design of Experiments (DOE) method and the Design-Expert statistical software. The performance of the proposed algorithm is evaluated by solving instances with different dimensions from OR-Library. The results of the proposed algorithm are compared with the solutions of CPLEX solver. The results show that the proposed SA can find near optimal solution in much less time than exact algorithm.
Sujit Kumar Jha,
Volume 23, Issue 3 (9-2012)
Abstract
This paper presents an overview of new approaches in rapid product development in production networks from design points of view. The manufacturing industries are changing their focus to global sourcing as a means to improve performance and enhance competitiveness. Some partnerships created with this strategy improve product development through collaborative design. With the advent of e-Commerce, a new set of collaborative applications integrated to the firms’ IT infrastructure allow a direct interaction between the firm and its suppliers, having an impact of negotiations. The globalization of the market necessitates the reduction of time-to-market, mainly due to shorter product life cycle. The computing and communication have become indispensable in every aspect of product development and design. The paper describes the network that directly links designer capabilities and with customers and manufacturing division. The networks focuses the three major forces that will affect the design community, namely, speed of decision, expansion of scope and degree of concurrency. Due to evolution of production networks, it has become possible to obtain the mass production within a key short time, using emerging technology that affect the speed and efficiency of product development using a pool of efficient designers and product managers.
Mehdi Khashei , Farimah Mokhatab Rafiei, Mehdi Bijari ,
Volume 23, Issue 4 (11-2012)
Abstract
In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficient once in financial markets. In this paper, the performance of four interval time series models including autoregressive integrated moving average (ARIMA), fuzzy autoregressive integrated moving average (FARIMA), hybrid ANNs and fuzzy (FANN) and Improved FARIMA models are compared together. Empirical results of exchange rate forecasting indicate that the FANN model is more satisfactory than other those models. Therefore, it can be a suitable alternative model for interval forecasting of financial time series.
Mahdi Bashiri, Hamidreza Rezaei,
Volume 24, Issue 1 (2-2013)
Abstract
In this paper, we propose an extended relocation model for warehouses configuration in a supply chain network, in which uncertainty is associated to operational costs, production capacity and demands whereas, existing researches in this area are often restricted to deterministic environments. In real cases, we usually deal with stochastic parameters and this point justifies why the relocation model under uncertainty should be evaluated. Albeit the random parameters can be replaced by their expectations for solving the problem, but sometimes, some methodologies such as two-stage stochastic programming works more capable. Thus, in this paper, for implementation of two stage stochastic approach, the sample average approximation (SAA) technique is integrated with the Bender's decomposition approach to improve the proposed model results. Moreover, this approach leads to approximate the fitted objective function of the problem comparison with the real stochastic problem especially for numerous scenarios. The proposed approach has been evaluated by two hypothetical numerical examples and the results show that the proposed approach can find better strategic solution in an uncertain environment comparing to the mean-value procedure (MVP) during the time horizon.
Ali Shahandeh Nookabadi, Mohammad Reza Yadoolahpour, Soheila Kavosh,
Volume 24, Issue 1 (2-2013)
Abstract
Network location models comprise one of the main categories of location models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network location problem, nodes represent demand points and candidate locations to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility Location Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of facility location and NDP (Network Design Problem) hence, called FLNDP (Facility Location Network Design Problem), a more general variant of FLP. In previous studies of this problem, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and location of facilities with low utilization. Furthermore, facility location cost (link construction cost) in the proposed model is supposed to be a function of the associated facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.
Yahia Zare Mehrjerdi, Tahereh Aliheidary,
Volume 25, Issue 1 (2-2014)
Abstract
Job Satisfaction (JS) plays important role as a competitive advantage in organizations especially in helth industry. Recruitment and retention of human resources are persistent problems associated with this field. Most of the researchs have focused on the job satisfaction factors and few of researches have noticed about its effects on productivity. However, little researchs have focused on the factors and effects of job satisfaction simultanosly by system dynamics approaches.In this paper, firstly, analyses the literature relating to system dynamics and job satisfaction in services specially at a hospital clinic and reports the related factors of employee job satisfaction and its effects on productivity. The conflicts and similarities of the researches are discussed and argued. Then a novel procedure for job satisfaction evaluation using (Artificial Neural Networks)ANNs and system dynamics is presented. The proposed procedure is implemented for a large hospital in Iran. The most influencial factors on job satisfaction are chosen by using ANN and three differents dynamics scenarios are built based on ANN's result. . The modelling effort has focused on evaluating the job satisfaction level in terms of key factors which obtain from ANN result such as Pay, Work and Co-Workers at all three scenarios. The study concludes with the analysis of the obtained results. The results show that this model is significantly usfule for job satisfaction evaluation
Keywords: Job Satisfaction, system dynamics, Artificial Neural Network (ANN), healthcar field.
Laya Olfat, Maghsoud Amiri, Jjahanyar Bamdad Soofi, Mostafa Ebrahimpour Azbari,
Volume 25, Issue 2 (5-2014)
Abstract
Having a comprehensive evaluation model with reliable data is useful to improve performance of supply chain. In this paper, according to the nature of supply chain, a model is presented that able to evaluate the performance of the supply chain by a network data envelopment analysis model and by using the financial, intellectual capital (knowledge base), collaboration and responsiveness factors of the supply chain. At the first step, indicators were determined and explained by explanatory Factor Analysis. Then, Network Data Envelopment Analysis (NDEA) model was used. This paper is the result of research related to supply chain of pharmaceutical companies in Tehran Stock Exchange and 115 experts and senior executives have been questioned as sample. The results showed that responsiveness latent variable had the highest correlation with supply chain performance and collaborative, financial and intellectual capital (knowledge base) latent variables were respectively after that. Four of the twenty eight supply chains which were studied obtained 1 as the highest performance rate and the lowest observed performance was 0.43.
Mr Aliakbar Hasani, Mr Seyed Hessameddin Zegordi,
Volume 26, Issue 1 (3-2015)
Abstract
In this study, an optimization model is proposed to design a Global Supply Chain (GSC) for a medical device manufacturer under disruption in the presence of pre-existing competitors and price inelasticity of demand. Therefore, static competition between the distributors’ facilities to more efficiently gain a further share in market of Economic Cooperation Organization trade agreement (ECOTA) is considered. This competition condition is affected by disruption occurrence. The aim of the proposed model is to maximize the expected net after-tax profit of GSC under disruption and normal situation at the same time. To effectively deal with disruption, some practical strategies are adopted in the design of GSC network. The uncertainty of the business environment is modeled using the robust optimization technique based on the concept of uncertainty budget. To tackle the proposed Mixed-Integer Nonlinear Programming (MINLP) model, a hybrid Taguchi-based Memetic Algorithm (MA) with an adaptive population size is developed that incorporates a customized Adaptive Large Neighborhood Search (ALNS) as its local search heuristic. A fitness landscape analysis is used to improve the systematic procedure of neighborhood selection in the proposed ALNS. A numerical example and computational results illustrate the efficiency of the proposed model and algorithm in dealing with global disruptions under uncertainty and competition pressure.
Eng Fateme Zare Baghabad, Dr Hassan Khademi Zare,
Volume 26, Issue 3 (9-2015)
Abstract
In this paper an efficient three- stage algorithm is developed for software production cost and time estimation. First stage includes a hybrid model composed of COCOMO and Function Points methods to increase estimation accuracy. Second stage encompasses paired comparisons matrix of analytical hierarchy process to determine amount of any resources consumed in each step of software production by experts’ opinions. Third stage concludes cost and time tables of production scheduling by using Work break structure (WBS) and network models of project control. In whole of all stages of this paper, triangular fuzzy numbers are used to express uncertainty existed in succession and repetition of each production step, time of beginning, ending, the duration of each task and costs of them. Retrieved results examined by 30 practical projects conclude accuracy of 93 percent for time estimation and 92 percent for cost one. Also suggested algorithm is more accurate than COCOMOІІ 2000 algorithm as 50 percent based on examined problems.
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