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Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty

Copyright © 2011. 36 pages.
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DOI: 10.4018/978-1-61520-633-9.ch004|
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MLA

Georgiadis, Michael C. and Pantelis Longinidis. "Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty." Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods. IGI Global, 2011. 73-108. Web. 26 Nov. 2014. doi:10.4018/978-1-61520-633-9.ch004

APA

Georgiadis, M. C., & Longinidis, P. (2011). Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty. In I. Minis, V. Zeimpekis, G. Dounias, & N. Ampazis (Eds.) Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods (pp. 73-108). Hershey, PA: Business Science Reference. doi:10.4018/978-1-61520-633-9.ch004

Chicago

Georgiadis, Michael C. and Pantelis Longinidis. "Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty." In Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods, ed. Ioannis Minis, Vasileios Zeimpekis, Georgios Dounias and Nicholas Ampazis, 73-108 (2011), accessed November 26, 2014. doi:10.4018/978-1-61520-633-9.ch004

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Abstract

This chapter considers a detailed mathematical formulation for the problem of designing supply chain networks comprising multiproduct production facilities with shared production resources, warehouses, distribution centers and customer zones and operating under time varying demand uncertainty. Uncertainty is captured in terms of a number of likely scenarios possible to materialize during the life time of the network. The problem is formulated as a mixed-integer linear programming problem and solved to global optimality using standard branch-and-bound techniques. A case study concerned with the establishment of Europe-wide supply chain is used to illustrate the applicability and efficiency of the proposed approach. The results obtained provide a good indication of the value of having a model that takes into account the complex interactions that exist in such networks and the effect of inventory levels to the design and operation.
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Introduction

The “problem” of supply chain network design is very broad and means different things to different enterprises. It generally refers to a strategic activity that will take one or more of the following decisions (Shapiro, 1999):

  • Where to locate new facilities (be they production, storage, logistics, etc.).

  • Significant changes to existing facilities, e.g. expansion, contraction or closure.

  • Sourcing decisions – what suppliers and supply base to use for each facility

  • Allocation decisions – e.g. what products should be produced at each production facility; which markets should be served by which warehouses, etc.

These decisions aim in some way to increase shareholder value. This means that models are employed to try to exploit potential trade-offs. These may include (Shapiro, 2003):

  • i.

    Differences in regional production costs.

  • ii.

    Distribution costs of raw materials, intermediates and products.

  • iii.

    Differences in regional taxation and duty structures.

  • iv.

    Exchange rate variations.

  • v.

    Manufacturing complexity and efficiency (related to the number of different products being produced at any one site).

  • vi.

    Network complexity (related to the number of different possible pathways from raw materials to ultimate consumers).

Most companies do not aim to quantify the latter two explicitly, but rather employ policies (e.g. single-sourcing of customer zones; exclusive product-plant allocation) to simplify operation to the desired degree.

A relatively rare instance of this class of problems is the “greenfield” design of a new supply chain where no significant assets exist at the time of the analysis (e.g. design of a future hydrogen infrastructure). A more common instance occurs when part of the infrastructure already exists, and a retrofit activity is being undertaken, where products may be re-allocated between sites, manufacturing resources may be restructured, the logistics network may be restructured, etc.

Models for the design and operation of supply chain networks may be steady-state or dynamic and may be deterministic or deal with uncertainties (particularly in product demands). Research in this field started very early on, with location-allocation problems forming part of the early set of “classical” operations research problems, see e.g. Geoffrion and Graves (1974) who consider the problem of distribution system layout and sizing and DC-customer allocation. It was recognised early on that systematic, optimisation-based approaches should be used, and that “common-sense” heuristics might lead to poor solutions (Geoffrion and van Roy, 1979). These early models tended to focus on the logistics aspects. Clearly, much more benefit could be achieved by simultaneously considering the production aspects and other issues related to integration of inventory, transportation, supplier selection, and investment budgeting decisions (Melo, Nickel and Saldanha da Gama, 2006).

Almost in the begging of 90’s the concept of supply chain began to emerge as one of the most popular field of research and study until today. Chopra and Meindl (2004) describe the supply chain as a dynamic network of collaboration that consists of many parties such as suppliers, manufacturers, transporters, warehouses, distribution centers, retailers, customers etc. and its objective is to maximize the overall value generated for all the members of supply chain.

Since companies recognized the potential competitive advantages, gained through a holistic management of their supply chain, the academic community has been developing several models that describe their design and operation. Flexibility, supplier selection and coordination of supply chain members are the most popular current issues in the field.

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Complete Chapter List

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Table of Contents
Chapter 1
Vassilios Vassiliadis, Giorgos Dounias
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Paolo Renna, Pierluigi Argoneto
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Coalitional Added Services in a Linear Neutral e-Marketplace: An Approach Based on the Shapley Value
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Chapter 3
Pierluigi Argoneto, Paolo Renna
The cooperation among firms allows them to focus on their core products, improving efficiency and competiveness. The emerging paradigm of... Sample PDF
Investing in Excess Capacity: Combining Real Options and Fuzzy Approaches in a Co-Opetitive Network
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Chapter 4
Michael C. Georgiadis, Pantelis Longinidis
This chapter considers a detailed mathematical formulation for the problem of designing supply chain networks comprising multiproduct production... Sample PDF
Optimal Design and Operation of Supply Chain Networks under Demand Uncertainty
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Chapter 5
Nicholas Ampazis
Estimating customer demand in a multi-level supply chain structure is crucial for companies seeking to maintain their competitive advantage within... Sample PDF
A Computational Intelligence Approach to Supply Chain Demand Forecasting
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Chapter 6
Seán McGarraghy, Michael Phelan
Contributions to a supply chain’s overall cost function (such as the bullwhip effect) are sensitive to the different players’ ordering policies.... Sample PDF
Generating Supply Chain Ordering Policies using Quantum Inspired Genetic Algorithms and Grammatical Evolution
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Chapter 7
Dimitrios Vlachos
As the practices of offshoring and outsourcing force the supply chain networks to keep on expanding geographically in the globalised environment... Sample PDF
Quantitative Risk Management Models for Newsvendor Supply Chains
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Chapter 8
Soumia Ichoua
Logistics area is often recognized as one of the key elements in achieving effective disaster preparedness and response efforts. This chapter... Sample PDF
Relief Distribution Networks: Design and Operations
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Chapter 9
Dimitrios M. Emiris, Athanasios Skarlatos
One of the most important, complicated and expensive processes in a warehouse is order-picking. The cost associated with order preparation and... Sample PDF
An Analytical Model to Estimate the Optimum Production Rate of Picking Processes in a Modular Warehouse Environment
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Chapter 10
Alexandros Xanthopoulos, Dimitrios E. Koulouriotis
This research explores the use of a hybrid genetic algorithm in a constrained optimization problem with stochastic objective function. The... Sample PDF
Constrained Optimization of JIT Manufacturing Systems with Hybrid Genetic Algorithm
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Chapter 11
Theodore Athanasopoulos, Ioannis Minis
Appointment-based logistics systems, such as special courier services, or repair / maintenance services, face ever increasing competitive pressures... Sample PDF
Multi-period routing in Hybrid Courier Operations
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