HAL Id: hal-01154605
https://hal.archives-ouvertes.fr/hal-01154605
Submitted on 28 May 2015
HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entic research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.
L’archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diusion de documents
scientiques de niveau recherche, publiés ou non,
émanant des établissements d’enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.
Sustainable supply chain network design: An
optimization-oriented review
Majid Eskandarpour, Pierre Dejax, Joe Miemczyk, Olivier Péton
To cite this version:
Majid Eskandarpour, Pierre Dejax, Joe Miemczyk, Olivier Péton. Sustainable supply chain
network design: An optimization-oriented review. Omega, Elsevier, 2015, 54, pp.11-32.
�10.1016/j.omega.2015.01.006�. �hal-01154605�
Sustainable supply chain network design: an
optimization-oriented review
Majid Eskandarpour
1
Pierre Dejax
1
Joe Miemczyk
2,3
Olivier P´eton
1
1
Ecole des Mines de Nantes, IRCCyN UMR CNRS 6597
(Institut de Recherche en Communications et Cybern´etique de Nantes), Nantes, France
email: {majid.eskandarpour, pierre.dejax, olivier.peton}@mines-nantes.fr
2
Audencia Nantes School of Management, 44312 Nantes, France
3
Aix Marseille Universit´e, CRET-LOG EA 881, 13625, Aix en Provence, France
email: jmiemczyk@audencia.com
January 2015
1 Introduction
Supply chain management has become a strategic issue for any company looking to meet targets in
terms of economic competitiveness, time and quality of service especially in an economic environment
characterized by the globalization of trade and the acceleration of industrial cycles. The trade press
is replete with examples of logistics network configuration, re-configuration, re-organization, mergers,
outsourcing, and so on. These developments have been influenced by successive trends in the economy
and society resulting from computerization, increased complexity of trade flows, increased competition
and certainly not least, sustainable development. Thus the strategic design and planning of logistics
networks is a topic that is becoming more important for businesses and researchers alike. Supply chain
network design is at the intersection of disciplines such as management, strategy, logistics, operations
research and as such, there is a significant challenge to researchers to consolidate and synthesize the
research in this field, which leads to the focus of this paper.
Supply Chain Management (SCM) spans all movements and storage of raw materials, work-in-process
inventory, and finished goods from the point-of-origin to the point-of-consumption [Simchi-Levi et al.,
2004]. It encompasses three decision levels: strategic, tactical and operational. In particular, at the
strategic level, Supply Chain Design comprises the decisions regarding the number and location of pro-
duction and storage facilities, the amount of capacity at each facility, the conciliation of market demand,
and decisions on supplier selection from a total cost perspective [Chopra and Meindl, 2004]. From an
operations research point of view, Supply Chain Network Design (SCND) is the discipline used to de-
termine the optimal location and size of facilities and the flow through the facilities [Autry et al., 2013].
As recalled in Zanjirani Farahani et al. [2014], “there are many models in the SCND literature. Different
decisions are made in the SCND and perhaps the most critical one is locating the facilities in different
tiers of the supply chain”.
Fifty years ago, the seminal paper by Hakimi [1964] generalized the original Weber problem [Weber and
Peik, 1909] from a single facility location problem to a multiple facility location problem. This publication
marked a revival of the facility location problem, which has become one of the standard problems in the
operations research community. Recent years have been characterized by a rapid enrichment of these
1
mathematical model solutions. Rich models now handle multiple levels in the logistics network, multiple
periods, products, technologies, transportation modes and types of facilities. They integrate capacity
constraints, tactical decisions and complex product flows. Thus, Supply Chain Network Design (SCND)
can be considered as the meeting point of the academic facility location problem and the real-life SCND
problem.
As already mentioned, among the major trends in SCM, the principles of sustainable development
have spread across the scientific literature. Current research mainly consists of assessing SCM policies
according to a triple bottom line including economic aspects, environmental performance and social
responsibility. Sustainable SCM has been the subject of numerous survey papers in both qualitative
and quantitative disciplines. A number of review papers have been published in recent years, which
relate to major trends in Supply Chain Management and investigate and suggest research opportunities.
Importantly, research in sustainable SCND has hardly been reviewed at all. However, the integration of
sustainability into SCND may change the locations of production facilities and inventories (see for example
Figures 12–14 in You and Wang [2011]) and therefore have a significant impact on the environment and
society. The goal of this paper is to bridge this gap.
More precisely, our objective is to review SCND problems that include a clear assessment of at least two
of the three dimensions of sustainable development: economic aspects, environmental performance and
social responsibility. We review papers containing mathematical models (linear and nonlinear programs
with integer or mixed-integer variables) with binary decision variables modeling the selection of candidate
facilities.
Our research questions can be briefly stated as follows: (i) which environmental and social criteria are
considered in sustainable SCND research? (ii) how are they integrated into mathematical models? (iii)
which optimization methods and tools are used? (iv) which real-life applications of sustainable SCND
are described in the scientific literature?
Section 2 describes the methodology adopted for the collection of research papers and compares our
work with existing reviews on related topics. SCND problems with environmental and social aspects
are investigated in sections 3 and 4, respectively. In section 3, we give a special focus on LCA-based
methods and review the scope of the environmental assessment, the environmental criteria used and the
metrics chosen to evaluate these criteria. The section 5 reviews the mathematical models. We used
3 main classification dimensions: mono-objective versus multi-objective models, linear vs non linear,
deterministic vs stochastic. The solution methods are described in section 6, which lists the use of
solvers, other exact methods and heuristic or metaheuristic approaches. We devote section 7 to the
description of case studies and real-life applications of sustainable SCND. The references are classified
according to the type of economic activity and the nature of the data. Finally, in section 8 we conclude
and suggest a number of future research directions.
2 Review methodology
2.1 Delimitations and search for literature
A comprehensive search of related research from 1990 to 2014 was applied to produce a synthesis of
peer-reviewed literature. The start of the time period was chosen such that the Brundtland Report of
the World Commission on Environment and Development [Burton, 1987] served as a starting point, in a
similar way to Seuring and M¨uller [2008] and Chen et al. [2014].
We searched papers published in international peer-reviewed journals from the main electronic bib-
liographical sources (Scopus, Web of Science) using keywords such as sustainable development, green,
environmental or social along with classic keywords such as supply chain, network design or facility
location in the titles or the topics covered. We use back-tracking to find earlier relevant sources, and
forward-tracking in Web of Science to find literature that are referring to the central sources. We also
2
looked for recent surveys in related domains in order to find additional sources including a few conference
papers.
From the collected material, we filtered the papers according to the following rules: (i) the papers
must be written in English language, (ii) they include decision variables modeling the location or selection
of candidate facilities, (iii) the measure of environmental or social impact is explicit either in the objective
function or in the constraints of the model.
From the second rule, we excluded a large number of articles dealing with the routing of product flows
in an already defined network. This is the case, for example, in the paper by Ramos et al. [2014], in
which the authors present depot selection as an extension of their work. The third rule enabled us to filter
many papers in the field of reverse logistics and management of undesirable facilities. Reverse logistics
and closed-loop supply chain have become a major area of supply chain management. Several surveys
have been published in the last fifteen years (see for example the surveys by Fleischmann et al. [1997],
Dekker et al. [2004], Bostel et al. [2005], Pokharel and Mutha [2009] or the special issues [Guide and
Van Wassenhove, 2006a,b]). Clearly, the goal of reverse or closed-loop supply chain is closely related to
that of sustainable supply chain management. However, as explained in Srivastava [2008] (Figure 4), the
main optimization often relies on a single economic objective. Environmental and social dimensions are
generally not explicitly assessed, but the resolution of these problems evidently contributes to designing
sustainable supply chain networks.
Undesirable facilities are those facilities that have adverse effects on people or the environment. They
generate some form of pollution, nuisance, potential health hazard, or danger to nearby residents; they
also may harm nearby ecosystems [Melachrinoudis, 2011]. Thus, the modeling of SCND problems that
include undesirable facilities often implicitly include environmental or social aspects.
On that basis, 87 papers were identified. In the following, they are denoted as reference papers and
listed in a separate category in the reference list in the end of this review.
2.2 Position in the literature
As many review papers have been written in neighboring domains, we needed to check whether the scope
of the present paper was not already covered by the existing literature. Table 1 summarizes the reviews
published in related areas. The symbol in columns 2 means that the corresponding paper considers
facility location as a main topic. The symbols # and 5 mean that facility location is one topic among
others or is not studied in the paper. The symbols have the same meaning in further tables.
We can classify the review papers in two categories. The first category gathers papers dealing with
Supply Chain Management in general. In these papers, facility location is either not studied or is only
one feature among many others. For example, Brandenburg et al. [2014] mention network design as one
out of 13 application areas. They mention 13 papers in this area, all except one being published between
2010 and 2013. Seuring [2013] indicates that more than 300 articles have been published in the last
15 years on the topic of green or sustainable (forward) supply chains, only 36 articles of which apply
quantitative models. Note that the review by Barbosa P´ovoa [Barbosa-P´ovoa, 2014] concerns supply
chain management, but with a strong emphasis on supply chain network design. The second category
regroups review papers on SCND. Only 5 of them deal with sustainability.
Table 2 details the content of the reviews which could potentially cover the sections 3, 5 and 6 of our
work: LCA based approaches (column 4), optimization models (column 5) and optimization methods
(column 6). The last column reports the number of references also mentioned in the present review.
Several reviews are dedicated to one activity: chemical and process industries [Barbosa-P´ovoa, 2014,
Nikolopoulou and Ierapetritou, 2012], biomass-to-energy [De Meyer et al., 2014, Yue et al., 2014].
Boukherroub et al. [2012] focus on multi-criteria decision making models for supply chain design. They
point 42 papers with environmental or social concern, and 43 papers with facility location decisions, 12
of them having both characteristics. The broad review by Dekker et al. [2012] contains one section on
3
Table 1: Existing reviews in related areas. RL = Reverse Logistics, CL = Closed-Loop
Article Facility Sustainability Scope or
location special focus
Supply Chain Management
Srivastava [2007] # Green SCM, RL, CL
Awudu and Zhang [2012] # Biofuel SCM, uncertainty
Dekker et al. [2012] # Green logistics
Soysal et al. [2012] # Quantitative models, food logistics
Nikolopoulou and Ierapetritou [2012] # Chemistry
Boukherroub et al. [2012] # Multi-criteria models
Brandenburg et al. [2014] # OR models and methods
Masoumik et al. [2014] # RL,CL
Barbosa-P´ovoa [2014] # # Chemical process
Yue et al. [2014] # # Biomass-for-bioenergy
Arioglu Salmona et al. [2010] 5
Sarkis et al. [2011] 5 Green SCM
Ashby et al. [2012] 5
Miemczyk et al. [2012] 5 Purchasing
Seman et al. [2012] 5 Green SCM
Zailani et al. [2012] 5 Malaysia
Beske et al. [2013] 5 Dynamic capabilities, food industry
Seuring [2013] 5 Forward supply chain
Yusuf et al. [2013] 5 UK oil and gas supply chains
Ashby et al. [2012] 5
Seuring and M¨uller [2008] 5
Gupta and Palsule-Desai [2011] 5
Johnsen et al. [2012] 5
Supply Chain Network Design
Terouhid et al. [2012] Socially responsible location
Chen et al. [2014] Manufacturing
Devika et al. [2014] # Forward, RL,CL
Zanjirani Farahani et al. [2014] # Competitive SCND
Beamon [1998] 5
Owen and Daskin [1998] 5
Daskin et al. [2005] 5
M. and G. [2005] 5
Sahin and S¨ural [2007] 5
Ak¸calı et al. [2009] 5 RL,CL
Melo et al. [2009] 5
Aras et al. [2010] 5 RL,CL
Pati et al. [2013] 5 RL,CL, single objective
Hassini et al. [2012] # Metrics
De Meyer et al. [2014] # Biomass-to-bioenergy
4
![Figure 4: Conceptual framework of LCA [ISO, 2006]](/figures/figure-4-conceptual-framework-of-lca-iso-2006-16uzggkt.webp)
