Supply chain design and optimization: Challenges and opportunities
Introduction
Supply chains may be defined as an integrated network of facilities and transportation options for the supply, manufacture, storage, and distribution of materials and products. They vary considerably in size, complexity, and scale from industry to industry (Simchi-Levi, 2005, Shapiro, 2006, Chopra and Meindl, 2012). Standard elements of supply chains might involve suppliers, manufacturers, and distributors. In the physical dimension, these elements translate to processing facilities, factories, trucks, trains, sea-faring vessels, and warehouses (Fig. 1). An optimally designed supply chain should, through one or a variety of metrics, reflect the “best” configuration and operation of all of these elements. Therefore, it is in industry's best interest to optimize their supply chains in some manner (Wassick, 2009). However, optimizing a supply chain can be a technically challenging task, especially for large ones. Consider a global supply chain similar to that of Fig. 1. This supply chain is a large-scale, complex system that includes a variety of supply, production, and distribution facilities (Ottino, 2011). There will also be an assortment of transportation options with different lead times and methods (truck, barge, air, etc.) to link these entities together, creating an integrated network. Furthermore, the supply chain would be subject to a variety of uncertainties, such as supply disruption, global price changes of commodity goods, etc. Thus, there is great economic potential and practical need to optimally design and coordinate all activities of all supply chain entities to achieve seamless operation for large-scale and complex supply chains under uncertainty. Consequently, optimization models and methods for supply chain design and operations have been of great interest to industry and academia over the past decades (Papageorgiou, 2009, Grossmann, 2012, Barbosa-Póvoa, 2012, Chopra and Meindl, 2012).
Supply chain design has been an active research area in Process Systems Engineering (PSE). An increasing number of research articles on this topic published in high-profile journals reflects its importance. Fig. 2 shows the number of journal articles addressing the topic of supply chain(s) published in the last two decades in AIChE Journal, Chemical Engineering Research and Design, Chemical Engineering Science, Computers & Chemical Engineering, and Industrial and Engineering Chemistry Research, as well as their citations. These journals do not cover all of the publications by PSE researchers in the supply chain area, but these data illuminate general trends. Clearly, the topic of supply chains is of growing importance in the PSE research community.
There are a number of excellent review papers on process supply chain optimization (Shah, 2005, Papageorgiou, 2009, Barbosa-Póvoa, 2012, Barbosa-Povoa, 2014). Instead of reviewing the broad area of supply chain modeling and optimization, the scope of this paper is restricted to supply chain design and its integration with supply chain operations. As supply chains themselves can be quite large and complex, methods to optimally design them can lead to cumbersome modeling and computational challenges. Much effort has been expended on this front from a variety of different sources and angles, and part of this article is to communicate this work in the context of supply chain design. Furthermore, this work seeks to identify opportunities and challenges in supply chain design research. Enterprise-wide optimization (EWO) involves optimizing the operations of R&D, material supply, manufacturing, and distribution of a company to reduce costs and inventories (Grossmann, 2005), and can provide a key tool for the advancement of supply chain design. Additionally, the recent trends toward sustainability, especially in energy, presents clear opportunities for future supply chain design research. These two key opportunities will be more clearly described in the following sections, followed by a description of technical challenges to be overcome, including multi-scale challenges, multi-objective and sustainability challenges, and multi-player challenges.
The following section will describe these opportunities in detail. Section 3 will discuss the aforementioned three key technical challenges that we have identified in supply chain design research. A variety of different approaches to these challenges will be discussed, and modeling and computational challenges that have arisen within each area will be highlighted. We also present illustrative examples from the literature that uniquely address these challenges and provide platforms for future research.
Section snippets
Research opportunities for supply chain design
There are two key areas of research opportunities for supply chain design: EWO as well as energy and sustainability topics. Certainly energy and sustainability can be studied independently, but the two topics overlap considerably. Studying this overlap between them provides a richer, deeper understanding of the interactions between them. This understanding is key when designing and optimizing entities as large and complex as supply chains. Thus, in the remainder of this work, energy and
Research challenges for supply chain design
Despite various research advances in supply chain design, there are a number of research challenges. These include, but are certainly not limited to, multi-scale challenges, multi-objective and sustainability challenges, and multi-player challenges.
More challenges also exist in this space: for example, a suitable software infrastructure must be developed to deliver any solutions to decision makers in the field. However, on the fundamental supply chain design research side, these three
Conclusion
Globalization and technological advancement has connected industries, firms, and countries like never before, providing ample opportunity to improve or refine supply chain design. Some of the key opportunities we see for advancement of supply chain design stem from Enterprise-Wide Optimization (EWO) techniques and society's increasing interest in energy/sustainability topics. EWO can provide opportunities for modeling and optimizing supply chain designs. Furthermore, these opportunities are
Acknowledgements
We gratefully acknowledge the financial support from the Institute for Sustainability and Energy at Northwestern University (ISEN) and Argonne National Laboratory via a Northwestern-Argonne Early Career Investigator Award for Energy Research.
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