Shabnam Rezapour

Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives

The aim of this study is to propose a Fuzzy multi-criteria decision-making approach (FMCDM) to evaluate the alternative options in respect to the users preference orders. Two FMCDM methods are proposed for solving the MCDM problem: Fuzzy Analytic Hierarchy Process (FAHP) is applied to determine the relative weights of the evaluation criteria and the extension of the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) is applied to rank the alternatives. Empirical results show that the proposed methods are viable approaches in solving the problem. When the performance ratings are vague and imprecise, this Fuzzy MCDM is a preferred solution.

Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case

We have developed a stochastic mathematical formulation for designing a network of multi-product supply chains comprising several capacitated production facilities, distribution centres and retailers in markets under uncertainty. This model considers demand-side and supply-side uncertainties simultaneously, which makes it more realistic in comparison to models in the existing literature. In this model, we consider a discrete set as potential locations of distribution centres and retailing outlets and investigate the impact of strategic facility location decisions on the operational inventory and shipment decisions of the supply chain. We use a path-based formulation that helps us to consider supply-side uncertainties that are possible disruptions in manufacturers, distribution centres and their connecting links. The resultant model, which incorporates the cut-set concept in reliability theory and also the robust optimisation concept, is a mixed integer nonlinear problem. To solve the model to attain global optimality, we have created a transformation based on the piecewise linearisation method. Finally, we illustrate the model outputs and discuss the results through several numerical examples, including a real-life case study from the agri-food industry.

Strategic design of competing centralized supply chain networks for markets with deterministic demands

This paper develops an equilibrium model to design a centralized supply chain network operating in markets under deterministic price-depended demands and with a rival chain present. The two chains provide competitive products, either identical or highly substitutable, for some participating retailer markets. We model the optimizing behavior of these two chains, derive the equilibrium conditions, and establish the finite-dimensional variational inequality formulation, and solve it using a modified projection method. We provide properties of the equilibrium pattern in terms of the existence and uniqueness results. Our model also considers the impacts of the strategic facility location decisions on the tactical inventory and shipment decisions. Finally, we illustrate the model through a numerical example and discuss how the prices, costs, incomes, and profits behave with respect to key marketing activities, such as advertising, brand positioning, and brand loyalty.

Resilient supply chain network design under competition: A case study

This research, motivated by a real-life case study in a highly competitive automobile supply chain, experimentally studies the impact of disruption on the competitiveness of supply chains. The studied supply chain faces two major risks: disruption of suppliers and tough competition from competitors. Any disruption in upstream level of the supply chain leads to an inability to meet demand downstream and causes market share to be lost to the competitors. For such a setting, a resilient topology is redesigned that can recover from and react quickly to any disruptive incidents. To this aim, we speculate there are three policies that can be used to mitigate the disruption risk, namely keeping emergency stock at the retailers, reserving back-up capacity at the suppliers, and multiple-sourcing. The problem is addressed using a mixed integer non-linear model to find the most profitable network and mitigation policies. We design a piecewise linear method to solve the model. Based on the data extracted from an automotive supply chain, practical insights of the research are extracted in a controlled experiment. Our analysis suggests that implementing risk mitigation policies not only work to the advantage of the supply chain by sustaining and improving its market share but also benefit customers by stabilizing retail prices in the market. Using the case study, we analyze the contribution of each risk strategy in stabilizing the supply chains profit, market share, and retail price. Our analysis reveals that downstream “emergency stock” is the most preferable risk mitigation strategy if suppliers are unreliable.

Supply chain network design under oligopolistic price and service level competition with foresight

Abstract In this paper a new bi-level model for designing the network structure of a competitive supply chain (SC) is presented with anticipating variable prices and service levels competition in markets under stochastic price and service level dependent elastic demands with the presence of existing, external rivals. The network structure of the new entrant SC would be designed under the limited production capacity of its producers in a way to maximize its future capturable profit in the competitive markets. The network of the new SC is assumed to be set “once and for all” but further price and service level adjustments are possible. Outer part of this bi-level model deals with strategic decisions of SC network design. Given the SC network structure assigned by the outer model in each iteration, the inner equilibrium model determines the equilibrium retail prices and service levels. Finally, we illustrate the model through several numerical examples.

Strategic Design of Competing Supply Chain Networks for Inelastic Demand

A model for designing the network of a new entrant supply chain under inelastic demand and in the presence of pre-existing competing chains is proposed. These supply chains provide an identical product for a market area. The model considers the location of distribution centres and retail outlets on a discrete set of potential locations. The assumptions of the model are: (1) static competition between the new and pre-existing chains and (2) a probabilistic customer behaviour based on an attraction function depending on both the location and the quality of the retailers. This model also incorporates the impact of the facilities’ location decisions on the operational inventory and shipment decisions. The resulting model is formulated as a mixed integer non-linear programme (MINLP). To solve the MINLP it is transformed to a linear one. We illustrate the model, discuss the results of a real-world case, and investigate the effectiveness of the proposed algorithm using randomly generated examples.

A machine-to-loop assignment and layout design methodology for tandem AGV systems with single-load vehicles

In this paper, we propose a method for design of tandem automated guided vehicle (AGV) systems with single-load vehicles. We consider the concurrent design of machines layout and AGV guide paths for a tandem system. Our goal is to devise a method that can achieve the following objectives: (1) maximise the workload balance between loops; (2) minimise the inter-loop flow; and (3) minimise the total flow distance. Our method solves the problem in four stages, considering the machines layout and the tandem paths at the same time. It assigns machines to loops, determines the layout of each loop, arranges loops on the floor, and finally designs a transportation centre to link the loops. We compare the performance of our method with a sequential design method that first determines the layout and then assigns the machines to loops. We solve a number of randomly generated problems for both methods. Results indicate that the proposed algorithm performs faster and achieves lower values of inter-loop flows and inter-loop flow distances.

Robust Supply Chain Network Design by Considering Demand-Side Uncertainty and Supply-Side Disruption

In this paper we propose a method that includes stochastic and robust models for designing the network structure of a three-tiered supply chain involving suppliers, manufacturers and retailers under random demands of markets and by considering disruption probabilities in the procurement facilities and connecting links of the chain. Demands of the markets are as assumed to be random variables with normal distribution and the disruption of the chain is formulated by defining different scenarios. Having substitutable facilities and extra production capacities makes it possible to overcome the negative effects of demand fluctuations and disruption of facilities. First we determine the optimal number, location and capacity of facilities in the first and third tiers and the best flow of material and product throughout the chain in a way to maximize the expected profit from the chain. Then to reduce the difference between the performances of the chain in different scenarios, we propose the ISP-Robust technique based on P-Robust technique to make the model robust. We discuss the differences and advantages of this technique in comparison to the P-Robust technique. We illustrate our method using data from the petrochemical industry.Copyright

Supply chain sustainability and raw material management : concepts and processes

Many organizations find supply chain management an essential prerequisite to building a sustainable competitive edge for their services or products. While interest in SCM is enormous, lack of theoretical frameworks and real world applications often characterizes research in the field, and effective management of the supply chain remains elusive. Supply Chain Sustainability and Raw Material Management: Concepts and Processes is a comprehensive and up-to-date resource for operations researchers, management scientists, industrial engineers, and other business practitioners and specialists looking for systemic and advanced discussions of supply chain management. By presenting qualitative concepts, quantitative models, and case studies, this book is a coherent guide to creating long-term and sustainable performance for organizations who want to compete in the global market.

Application of Self Organizing Map (SOM) to model a machining process

Purpose – This paper aims to present a practical application of Self Organizing Map (SOM) and decision tree algorithms to model a multi‐response machining process and to provide a set of control rules for this process.Design/methodology/approach – SOM is a powerful artificial neural network approach used for analyzing and visualizing high‐dimensional data. Wire electrical discharge machining (WEDM) process is a complex and expensive machining process, in which there are a lot of factors having effects on the outputs of the process. In this work, after collecting a dataset based on a series of designed experiments, the paper applied SOM to this dataset in order to analyse the underlying relations between input and output variables as well as interactions between input variables. The results are compared with the results obtained from decision tree algorithm.Findings – Based on the analysis of the results obtained, the paper extracted interrelationships between variables as well as a set of control rules fo...