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Showing 102 results for Supply Chain
An Additive Weighted Fuzzy Programming for Supplier Selection Problem in a Supply Chain
A. Amid, S.h. Ghodsypour,
Volume 19, Issue 4 (12-2008)
Abstract

  Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer’s company. Supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision making complicated. Simultaneously, in this model, vagueness of input data and varying importance of criteria are considered. In real cases, where Decision- Makers (DMs) face up to uncertain data and situations, the proposed model can help DMs to find out the appropriate ordering from each supplier, and allows purchasing manager(s) to manage supply chain performance on cost, quality, on time delivery, etc. An additive weighted model is presented for fuzzy multi objective supplier selection problem with fuzzy weights. The model is explained by an illustrative example.


On the Bullwhip Effect Measure in Supply Chains with VAR (1) Demand Process
S.k. Charsoghi, A. Sadeghi,
Volume 19, Issue 4 (12-2008)
Abstract
In this paper, a two-echelon supply chain, which includes two products based on the following considerations, has been studied and the bullwhip effect is quantified. Providing a measure for bullwhip effect that enables us to analyze and reduce this phenomenon in supply chains with two products is the basic purpose of this paper. Demand of products is presented by the first order vector autoregressive time series and ordering system is established according to order up to policy. Moreover, lead-time demand forecasting is based on moving average method because this forecasting method is used widely in real world. Based on these assumptions, a general equation for bullwhip effect measure is derived and there is a discussion about non-existence of an explicit expression for bullwhip effect measure according to the present approach on the bullwhip effect measure. However, bullwhip effect equation is presented for some limited cases. Finally, bullwhip effect in a two-product supply chain is analyzed by a numerical example.
A Mathematical Method for Managing Inventories in a Dual Channel Supply Chain
H. Teimory, H. Mirzahosseinian, A. Kaboli,
Volume 19, Issue 4 (12-2008)
Abstract

  The advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. In this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. The system receives stochastic demand from the both channel which each channel has an independent demand arrival rate. A lost-sales model which no backorder is allowed is supposed. The replenishment lead times are assumed independent exponential random variables for both warehouse and the retail store. Under the replenishment inventory policy, the inventory position is kept constant at a base-stock level. To analyze the chain performance, an objective function included holding and lost sales costs is defined. At the end, a proposed algorithm named, Best Neighborhood (BN) is used to find a good solution for inventory and the results are compared with Simulated Annealing (SA) solutions.


An Adaptive Neuro Fuzzy Inference System for Supply chain Agility Evaluation
J. Jassbi, S.m. Seyedhosseini , N. Pilevari,
Volume 20, Issue 4 (4-2010)
Abstract
Nowadays, in turbulent and violate global markets, agility has been considered as a fundamental characteristic of a supply chain needed for survival. To achieve the competitive edge, companies must align with suppliers and customers to streamline operations, as well as agility beyond individual companies. Consequently Agile Supply Chain (ASC) is considered as a dominant competitive advantage.  However, so far a little effort has been made for designing, operating and evaluating agile supply chain in recent years. Therefore, in this study a new approach has been developed based on Adaptive Neuro Fuzzy Inference System (ANFIS) for evaluating agility in supply chain considering agility capabilities such as Flexibility, Competency, Cost, Responsiveness and Quickness. This evaluation helps managers to perform gap analysis between existent agility level and the desired one and also provides more informative and reliable information for decision making. Finally the proposed model has been applied to a leading car manufacturing company in Iran to prove the applicability of the model.
A Fuzzy Approach For Multi-Objective Supplier Selection
F. Bagheri , M. J. Tarokh,
Volume 21, Issue 1 (6-2010)
Abstract
Assessment and selection of suppliers are two most important tasks in the purchasing part in supply chain management. Supplier selection can be considered to be a single or multi-objective problem. From another point of view, it can be a single or multi-sourcing problem. In this paper, an integrated AHP and Fuzzy TOPSIS model is proposed to solve the supplier selection problem. This model makes the decision-maker to be able to solve this problem with different criteria and different weight for each criterion with respect to the purchasing strategy. Finally, the proposed model is illustrated by an example.
A New Approach for Supplier Selection Process from the Features of Second Layer Suppliers Point of View
Mohammad Najafi Nobar, Mostafa Setak,
Volume 21, Issue 1 (6-2010)
Abstract
In nowadays world competitive market, on account of the development of electronic media and its influence on shortening distances, companies require some core competencies in order to be able to compete with numerous competitors in industry and sustain their situation in such a market. In addition companies achieve this target are those which their processes perform great and exploit from competitive price, quality, guarantee, etc. Since some parameters such as price and quality are so dependent on the performance of company supply chain management, so the results can highly impress the final price and quality of products. One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article two layers of suppliers have been considered as a chain of suppliers. First layer suppliers are evaluated by two groups of criteria which the first one encompasses criteria belongs to first layer suppliers features and the second group contains criteria belong to the characteristics of second layer suppliers. One of the criteria is the performance of second layer suppliers against environmental issues. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second layer suppliers features as a criteria for selecting the best supplier.
Using System Dynamics to Model Rod Bar Supply Chain in Iranian Market
Jafar Mahmodi , Mohamad Hosein Minaee,
Volume 21, Issue 3 (9-2010)
Abstract

  Steel market and particularly rod bar market play important roles in economy of countries. Economic systems are considered as complex systems which are sophisticated to be modeled mathematically. One way to model these systems is simulation and use of system dynamics. This paper models rod bar supply chain in Iran using system dynamics. Data of this research is gathered from first hand materials published by governmental sector. In order to modeling relationships between variables, interviews were conducted with experts in Iran Ministry of Commerce. Proposed model explains turbulence of rod bar market during 5 years ago and the fluctuations of its price. In addition, it is examined and confirmed by experts of this market in Iran Ministry of Commerce. Although proposed model may not offer an exact prediction of future market, but could be used as an applicable tool for analyzing and adjusting the market in Iran Ministry of Commerce .


Inventory Cost Evaluation Under VMI Program with Lot Splitting
Rasoul Haji, Mohammadmohsen Moarefdoost, Seyed Babak Ebrahimi,
Volume 21, Issue 4 (12-2010)
Abstract

  This paper aims to evaluate inventory cost of a Two-echelon serial supply chain system under vendor managed inventory program with stochastic demand, and examine the effect of environmental factors on the cost of overall system. For this purpose, we consider a two-echelon serial supply chain with a manufacturer and a retailer. Under Vendor managed inventory program, the decision on inventory levels are made by manufacturer centrally. In this paper, we assume that the manufacturer monitors inventory levels at the retailer location and replenishes retailer's stock under (r, n, q) policy moreover, the manufacturer follows make-to-order strategy in order to respond retailer's orders. In the other word, when the inventory position at the retailer reaches reorder point, r, the manufacturer initiates production of Q=nq units with finite production rate, p. The manufacturer replenishes the retailer's stock with replenishment frequency n, and the complete batch of q units to the retailer during the production time. We develop a renewal reward model for the case of Poisson demand, and drive the mathematical formula of the long run average total inventory cost of system under VMI. Then, by using Monte Carlo simulation, we examine the effect of environmental factors on the cost of overall system under VMI .


Capacitated Facility Location Problem with Variable Coverage Radius in Distribution System
M. S Jabalameli, B. Bankian Tabrizi, M. Moshref Javadi ,
Volume 21, Issue 4 (12-2010)
Abstract

  The problem of locating distribution centers (DCs) is one of the most important issues in design of supply chain. In previous researches on this problem, each DC could supply products for all of the customers. But in many real word problems, DCs can only supply products for customers who are in a certain distance from the facility, coverage radius. Thus, in this paper a multi-objective integer linear programming (MOILP) model is proposed to locate DCs in a two-echelon distribution system. In this problem, customers who are in the coverage radius of the DCs can be supplied. Moreover, we suppose that the coverage radius of each DC can be controlled by decision maker and it is a function of the amount of money invested on the DC. Finally, a random generated problem is used to verify the model and the computational results are presented .


Fuzzy Queuing Approach for Designing Multi Supplier Systems (Case: SAPCO Company)
E. Teimoury, H. Ansari , M. Fathi ,
Volume 22, Issue 1 (3-2011)
Abstract

  The importance of reliable supply is increasing with supply chain network extension and just-in-time (JIT) production. Just in time implications motivate manufacturers towards single sourcing, which often involves problems with unreliable suppliers. If a single and reliable vendor is not available, manufacturer can split the order among the vendors in order to simultaneously decrease the supply chain uncertainty and increase supply reliability. In this paper we discuss with the aim of minimizing the shortage cost how we can split orders among suppliers with different lead times. The (s,S) policy is the basis of our inventory control system and for analyzing the system performance we use the fuzzy queuing methodology. After applying the model for the case study (SAPCO), the result of the developed model will be compared in the single and multiple cases and finally we will find that order splitting in optimized condition will conclude in the least supply risk and minimized shortage cost in comparison to other cases .


Investigating Impact of Intelligent Agents in Improving Supply Chain Performance
F Etebari, M. Abedzadeh , F. Khoshalhan,
Volume 22, Issue 1 (3-2011)
Abstract
Improvement in supply chain performance is one of the major issues in the current world. Lack of coordination in the supply chain is the main drawback of supply chain that many researchers have proposed different methodologies to overcome it. VMI (Vendor-managed inventory) is one of these methodologies that implementing it has some obstacles. This paper proposes new model that is agent-managed SC. This paper is trying to use intelligent agent technology in the supply chain. In this paper supply chain assessment performance measure indicators have been divided into three categories cost, flexibility and customer responsiveness indicators. In the first category we use holding and backordered inventory costs, for second category, bullwhip effect are used and for the last one customer responsiveness indicator has been applied. Bullwhip effect is one of the main phenomena’s that has been tried to reduce it with the agent-based systems.
A Fuzzy Compromise Programming Solution for Supplier Selection in Quantity Discounts Situation
Behin Elahi, Seyed Mohammad Seyed-Hosseini, Ahmad Makui,
Volume 22, Issue 2 (6-2011)
Abstract

 

  Supplier selection,

  Multi-objective decision making,

  Fuzzy Compromise programming,

  Supply chain management,

  Quantity discount .

 

Supplier selection is naturally a complex multi-objective problem including both quantitative and qualitative factors. This paper deals with this issue from a new view point. A quantity discount situation, which plays a role of motivator for buyer, is considered. Moreover, in order to find a reasonable compromise solution for this problem, at first a multi-objective modeling is presented. Then a proposed fuzzy compromise programming is utilized to determine marginal utility function for each criterion. Also, group decision makers’ preferences have taken into account and the weight of each criterion has been measured by forming pair-wise comparison matrixes. Finally the proposed approach is conducted for a numerical example and its efficacy and efficiency are verified via this section. The results indicate that the proposed method expedites the generation of compromise solution .


Design of Distributed Optimal Adaptive Receding Horizon Control for Supply Chain of Realistic Size under Demand Disturbances
M. Miranbeigi, A.a. Jalali, A. Miranbeigi ,
Volume 22, Issue 3 (9-2011)
Abstract

 

  supply chain network

  receding horizon control demand move suppression term

 

Supply chain networks are interconnection and dynamics of a demand network. Example subsystems, referred to as stages, include raw materials, distributors of the raw materials, manufacturers, distributors of the manufactured products, retailers, and customers. The main objectives of the control strategy for the supply chain network can be summarized as follows: (i) maximize customer satisfaction, and (ii) minimize supply chain operating costs. In this paper, we applied receding horizon control (RHC) method to a set of large scale supply chains of realistic size under demand disturbances adaptively. Also in order to increase the robustness of the system , we added a move suppression term to cost function .


Complex Integrated Supply Chain Planning with Multiple Modes Supply, Production and Distribution by ELECTRE Method
M Karbasian, M Bashiri, M Safaei,
Volume 22, Issue 3 (9-2011)
Abstract

 

  Strategic programming, Complex supply chain, Lean, Production programming, Suppliers selection,

  ELECTRE

This paper represents a model of strategic programming with limited resources in a complex supply chain. The main goal of the proposed model is to increase efficiency and effectiveness of the supply chain with respect to income increases and cost decreases. Using special objective functions, has guaranteed the lean supply, production, distribution and suppliers' selection strategies. Furthermore, it can use for production programming in the supply chain. Moreover, customer satisfaction has also been perceived, by using minimization objective functions of shortage amount and restrictions of maximum allowed shortage. In this model, objective functions have been defined in a way, which directs the supply chain to the lean. Finally, after determining strategies according to objective functions and constraints, the optimal strategies using multi-criteria decision making - ELECTRE process- have been chosen .


Determination of a Desirable Inventory Policy in a three Echelon Multilayer Supply Chain with Normal Demand
Maghsoud Amiri, Mehdi Seif Barghy, Laaya Olfat, Seyed Hossein Razavi Hajiagha ,
Volume 23, Issue 1 (3-2012)
Abstract
Inventory control is one of the most important issues in supply chain management. In this paper, a three-echelon production, distribution, inventory system composed of one producer, a set of wholesalers and retailers is considered. Costumers' demands can be approximated by a normal distribution and the inventory policy is a kind of continuous review (R, Q). In this paper, a model based on standard cost structure of inventory systems is developed and a heuristic algorithm is designed to optimize the developed model. The application of model is examined in a series of designed experiments that are compared with simulation results. These comparisons verify the validity of the model. Regarding to real complexities in three-echelon systems analysis, the proposed method can have a wide application in practical problems with the same considerations and assumptions. In addition, this method can be used to approximate those systems that follow a Poisson demand.
A Complex Design of the Integrated Forward-Reverse Logistics Network under Uncertainty
, , ,
Volume 23, Issue 2 (6-2012)
Abstract
Design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the integrated logistics network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then, the stochastic counterpart of the proposed MILP model is used to measure the conditional value at risk (CVaR) criterion, as a risk measure, that can control the risk level of the proposed model. The computational results show the power of the proposed stochastic model with CVaR criteria in handling data uncertainty and controlling risk levels.
Introducing a New Formulation for the Warehouse Inventory Management Systems: with Two Stochastic Demand Patterns
Masoud Mahootchi, Taher Ahmadi, Kumaraswamy Ponnambalam,
Volume 23, Issue 4 (11-2012)
Abstract
This paper presents a new formulation for warehouse inventory management in a stochastic situation. The primary source of this formulation is derived from FP model, which has been proposed by Fletcher and Ponnambalam for reservoir management. The new proposed mathematical model is based on the first and the second moments of storage as a stochastic variable. Using this model, the expected value of storage, the variance of storage, and the optimal ordering policies are determined. Moreover, the probability of within containment, surplus, and shortage are computable without adding any new variables. To validate the optimization model, a Monte Carlo simulation is used. Furthermore, to evaluate the performance of the optimal FP policy, It is compared to (s*,S*) policy, as a very popular policy used in the literature, in terms of the expected total annual cost and the service level. It is also demonstrated that the FP policy has a superior performances than (s*,S*) policy.
Reconfiguration of Supply Chain: A Two Stage Stochastic Programming
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.
Price Competition Between Two Leader-Follower Supply Chains, A Case Study
Mohammad Azari Khojasteh, Mohammad Reza Amin-Naseri, Isa Nakhai Kamal Abadi,
Volume 24, Issue 4 (12-2013)
Abstract

We model a real-world case problem as a price competition model between two leader-follower supply chains that each of them consists of one manufacturer and one retailer. T he manufacturer produces partially differentiated products and sells to market through his retailer. The retailer sells the products of manufacturer to market by adding some values to the product and gains margin as a fraction of the all income of selling products. We use a two-stage Stackelberg game model to investigate the dynamics between these supply chains and obtain the optimal prices of products. We explore the effect of varying the level of substitutability coefficient of two products on the profits of the leader and follower supply chains and derive some managerial implications. We find that the follower supply chain has an advantage when the products are highly substitutable. Also, we study the sensitivity analysis of the fraction of requested margin by retailer on the profit of supply chains.


A Network data envelopment analysis model for supply chain performance evaluation: real case of Iranian pharmaceutical industry
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.
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