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Urban distribution centers' location selection's problem: A survey

Conference Paper · May 2015

DOI: 10.1109/ICAdLT.2015.7136635

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 Urban Distribution Centers’ Location Selection’s
Problem: A survey

Maroi Agrebi Mourad Abed Mohamed Nazih Omri

University of Valenciennes University of Valenciennes University of Monastir
and Hainaut-Cambresis and Hainaut-Cambresis MARS UR11ES57, FSM
University of Sfax LAMIH UMR CNRS 8201, UVHC mohamednazih.omri@fsm.rnu.tn
LAMIH UMR CNRS 8201, UVHC mourad.abed@univ-valenciennes.fr
MARS UR11ES57, FSM
maroi.agrebi@etu.univ-valenciennes.fr

Abstract—This paper provides a review on recent efforts and • The environmental effect of urban freight movements
development in urban distribution centers’ location selection’s (in terms of energy use and environmental impacts
problem in two categories including uncertain environment and such as pollution, noise, visual intrusion, etc.).
certain environment problems and their solution methods. Also,
it provides an overview on various objectives and criteria used.
While there are a few papers related to this topic, we have not
seen any comprehensive review papers that can cover it. We However, there are many negative effects and inefficient
believe this paper can be used as a complementary and updated activities, like congestion, pollution, the increase in the trans-
version. port cost, customer dissatisfaction, etc. That is why, freight
transport cannot exist without a system for urban flows man-
Keywords—location selection, urban distribution center, opti-
mization of freight transport, urban logistic, city logistics, certain agement. This system is very important to ensure the efficiency
environment, uncertain environment of freight transport system in the city, while reducing traffic
congestion and lessening environmental impacts, especially
with the complexity of the analysis of the urban logistics.
I. I NTRODUCTION
In today’s market circumstances, city logistics called also
urban logistic, have received growing attention in terms of Efficiency of urban goods delivery operation is one of the
level and impacts. Especially, because the cities have been most considered topic. For example, Hashim et al. [3] have
getting becoming denser with the enormous increase of freight treated the distribution centers’ location selection’s problem
transport. In fact, freight transport contributes an estimated under uncertain environment for minimizing cost and fulfill the
between 10% and 30% of the traffic flow in various cities [1], demand. Farahani et al. [4] have discussed urban transportation
but an estimated 40% in pollution and noise. City logistics is network design problems. The objective is to provide a general
the process for totally optimizing the logistics and transport view, structured and organized, about problems, definitions,
activities by private companies in urban areas while consider- classifications, objectives, constraints, variables for networks
ing the traffic environment, the traffic congestion and energy decision and resolution of the problem of urban transportation
consumption within the framework of a market economy. network design. Anand et al. [2] have proposed an ontology
In fact, its role is to cope with the sustainability problems named GenCLOn, which summarizes the delivery process of
encountered in urban freight transport [2]. the freight, in order to facilitate the stakeholders decision-
making. Kuo et al. [5] have treated optimizing goods assign-
The importance given to the matter of urban logistic refers ment and the vehicle routing problems with time-dependent
to the several reasons. Among the most significant are: travel speeds, taking into account the non-passing property,
which is neglected in most research previous, for the travel
• It is fundamental to sustain our existing life style. time calculation.
• The role it plays in servicing and retaining indus-
trial and trading activities, which are essential major,
After having discussed the city logistic’s importance, its
wealth generating activities.
negative effects and inefficient activities and the problems
• The contribution that an efficient freight sector makes covered in this topic, we shall investigate urban distribution
to the competitiveness of industry in the region con- centers’ location selection’s problem. The organization of the
cerned. rest of this paper is organized as follows. In the first part,
an overview on the issue in question is given. In this first
• The effect of freight transport and logistics costs on
part, we present urban ditribution center’s utility, benefits
the cost of commodities consumed in the region.
and critical success factors. Then, we discuss the existing
• The total cost of freight transport and logistics is researches related to the urban distribution centers’ location
significant and has a direct bearing on the efficiency selection. In the second part, we synthesize the set of inflential
of the economy. criteria involve into the process of selection.
 II. U RBAN DISTRIBUTION CENTERS ’ LOCATION • Distance of the parking bay from the shop.
SELECTION ’ S PROBLEM : A N OVERVIEW
In fact, urban distribution center is common problem
Indeed, the functioning of a city means an important rate encountered by logistic managers [13]. In this article, we are
of trade in goods. This need for service relies on physical interested by its location selection.
facilities, like plants, distribution centers, collection centers,
etc., as shown in the following figure (fig. 1). These facilities
are the real drivers of the urban logistics system. Therefore, the B. Urban distribution centers’ location selection’s problem
location selection of these facilities strongly attracted attention
as a major problem of urban logistics. In this article, we Over the past decades, urban distribution centers’ loca-
are interested by urban distribution centers as the most of tion selection’s problem have been investigated by several
important logistic facilities and its location. researchers. This problem is concerned with how to select
urban distribution centers from the potential set built while
respecting and satisfying a set of criteria such as the investment
cost, the possibility of expansion, the availability of acquisition
hardware, human resources, proximity to suppliers, etc.
The following figure (Fig 2) presents an illustrative ex-
ample of our problem. A certain number of decision-makers
determine the number of urban distribution centers desired in
order to locate them. Then, they select one or more urban
distribution centers among a certain number of centers poten-
tial, on the basis of performance history of each center. Urban
distribution centers selected will be subsequently integrated in
the supply chain.

Fig. 1. A generic supply chain network [6]

A. Urban distribution centers

In terms of logistical system design and administration, the
urban distribution center is defined as a platform of bundling-
unbundling, generally lying a few kilometres from downtown,
whose first goal is the management of flows of dense areas [7].
It is viewed as the competency that links an entreprise with
its customers and suppliers [8,9] to facilate the movements of
goods [3]. The aim of which is to receive a demand of the
market and sending commands to the suppliers as its stock
management strategist.
The main benefits of urban distribution centers are [9]:
firstly, reductions in the number of vehicle trips, secondly,
reductions in the number of vehicle kilometres, and then better
utilization rates for vehicles. A higher load factor in the city
can decrease harmful effects associated with city logistics.
In the literature, there are eight critical success factors for
an urban distribution center [11, 12]:
• Location in/near the city,
Fig. 2. Example of urban distribution centers’ location selection’s problem
• Subsidy collection,
The location of urban distribution center is one of the most
• Collaboration with shipper and freight carriers, important decision issues for logistic managers [8, 13]. The
• Financial viable, kind of problem can be classified as an exceptional case of
the more general facility location problem. It is considered as
• Service cost of the UDC, a crucial in the design of efficient logistics systems which have
• Access permit cost, direct impact on the efficiency of logistics systems [15] and is
an important factor in the improvement of the logistic process
• Delay in delivery time, in the cities.
 In the literature, many researches have tried to treat the in a variable pollution cost caused by travels of vehicles, a
problem in question by using different proposed methods. In variable pollution cost caused by logistics platforms and a
the rest of this paper, we present the most of these researches, variable congestion cost due to both vehicles and platforms.
which we classify them into two categories according to the As regards the social point of view, they were concentrated in
environment of problem treatment as uncertain environment the acceptability by inhabitants near logistics platforms and the
and certain environment. A comparison between the existing acceptability by inhabitants impacted by vehicles movements.
methods is given by the table I. Therefore, the authors have developed a generic optimization
tool able to create, compute and evaluate different scenarios
The researches which have treated the problem under cer- in any urban area, using the commercial software IBM ILOG
tain environment, there have considered the problem’s param- CPLEX12.1. The authors have applyed the model in the case
eters, like the client demand, investment cost, transportation of Marseille. Preliminary results found from this case seem
cost, etc., as being fixed and known in advance. Crainic et al. to prove the interest of the tool and the concordance of the
[1] have provided a classic mathematical model, in which they model. For future research, the authors have suggested an
have taken into account the multiplicity of goods transported. accurate qualitative study dedicated to the city of Marseille,
The authors aim to optimize the fixed cost of opening and with assessment and comparison of the different possible
operation of urban distribution centers as well as the cost of scenarios.
transport between external areas and satellites and satellites
and commercial areas. The constraints was used in proposed Fei et al. [19] have applied the genetic algorithm whose
model are as following : constraint which are related to the goal is to choose a number of urban distribution centers to min-
level of truck traffic, and others which are related to the imize the total cost of transport which includes the investment
capacity of truck and city-freighters. In this research, the case cost, variable cost and fixed cost. The selection criteria are:
of the city of Rome has been presented, in order to validate First, the natural environment including climate, geography,
the proposed method. In this case, the authors have chosen to pollution and so on. Second, the business environment such as
treat one type of freight and truck in a time interval equal to freight characteristics, logistic costs, and service quality. Third,
four hours. They have taken into account the socio-economic the infrastructure situation (transport and public institutions).
aspects of each commercial area (population, store number, Fourth, others such as using of land resource, regulations of
total store surface, etc.). For results, the wait time obtained is environmental protection and neighboring situation. By the
less than eight seconds by using branch and bound method. objective function, authors have wanted to minimize the trans-
The authors have suggested as perspectives the development portation cost (from the producer to distribution center and
of interactions between different stakeholders. from the urban distribution center to customers). Constraints
included in the model are as follows constraints related to the
Guyon et al. [16] have proposed a conceptual model which total quantity of freight transported, to the center distribution’s
contains : a catalogue of urban distribution center’s loca- capacity and to the customer requirements. In this research a
tions, like geographic location, maximum size, construction numerical example is presented which have showed that the
cost, etc., a catalogue of demand points such as geographic model proposed is fairly effective and robust.
area, number of packages, volume, etc., and a catalogue of
vehicles for example type of energy, total weight, purchase The researches mentioned above could only deal with
cost, emission of pollutants, etc. The authors have taken into urban distribution centers’ location’s selection problem under
account a single level of freight consolidation, an only one certain evironment. To solve this problem under uncertain
type of product and a single period of planning (during ten environment, new researches were proposed. In what follows,
years). The criteria used are classified into three aspects: we present the most of these researches.
the economic aspect which contains the costs of construc- Chen [8] has proposed a multicriteria decision making
tion of urban distribution centers and the cost of vehicles method based on fuzzy logic, whose goal is to reduce trans-
purchase. The environmental aspect includes the emission of portation cost, enforce operation efficiency and logistic per-
gaseous pollutants, noise pollution, and congestion rate. And formance. He has applied its method proposed in the case of
the social aspect brings the accessibility of the platforms and a company where there are three decision-makers and three
platforms settlement areas. For future research, the authors alternatives (potential sets). The criteria which are taken into
have suggested the improvement of the proposed model and the account in this case are as follows: investment cost, expan-
achievement of a mathematical model and a simulator, as well sion possibility, availability of acquirement material, human
as the experimentation of this model on the city of Marseille. resource and closeness to demand market. The application has
This case has the particularity of having an urban logistic area proved that the proposed method can determine the order of
in the heart of downtown with the urban distribution centre alternatives and the degree preferably between each pair of
called ARENC. alternatives. It has also showed that the method is adaptable
and effecient for treating subjective judgments in an uncertain
Guyon et al. [17, 18] have proposed an integer linear
environment. Chen has stated that this methodology is more
programing model, in which they have taken into account one
effecient than conventional approaches. In addition, he has
carrier (public or private), one route per vehicle, one vehicle
suggested the possibility of level changement of the linguistic
per zone of demand, transportation costs are estimated and
values and that the method can be performed easily with other
a limited platform lifecycle (3000 days). From an economic
aggregate functions to aggregate fuzzy ratings of decision-
point of view, the authors were interested in the fixed cost of
makers.
building or maintaining logistics platforms, the fixed cost of
purchasing vehicles and the variable cost of using vehicles. Awasthi et al. [20] have proposed a multi-criteria decision-
From an environmental point of view, they were interested making method based on the fuzzy logic and the technique for
 TABLE I. C OMPARATIVE TABLE OF EXISTING WORK

Environments Methods References

Certain Classic methods Classic mathematical model [1]
Model conceptual [16]
Integer linear programming model [17,18]
Genetic algorithm [19]
Uncertain Hybrid methods Multicriteria decision making method based on fuzzy logic [8]
Multicriteria decision making method based on fuzzy logic [20]
and technique for order of preference by similarity to ideal
solution (TOPSIS)
Multicriteria decision making method based on fuzzy theory [14]
Multi-objectives decision making model based on fuzzy [21]
theory
Multicriteria decision making method based on fuzzy logic [22]
and SWOT analysis

order of preference by similarity to ideal solution (TOPSIS), and the global optimal solution of programming can be easily
which is a multi-criteria decision analysis method. The goal obtained by the proposed method. This method is analysed by
of this research is to minimize distribution costs, to conform the sensitivity analysis to verify the influence of the optimism-
to sustainable freight regulations of the city and create least pessimism index on the solution found, where they find that the
negative effects on city residents and their environment. The objective function increases with the increase in the value of
selection criteria used are divided between cost criteria and the optimism-pessimism index and vice versa. This numerical
criteria profit. These criteria are as follows accessibility, secu- example used has illustrated the effectiveness of the proposed
rity, connectivity of the location with other modes of transport, model and solution approach.
cost, environmental impact, proximity to consumers, proxim-
ity to suppliers, the resource availability, freight regulations, Lee [22] has proposed a multi-criteria decision-making
possibility of expansion and quality of service. The authors method coupling fuzzy logic and SWOT analysis. The rating of
have validated the method proposed by its application on the the alternatives and the weight of the criteria are given in terms
case of a company, where there are three decisions makers and of linguistic variable. The criteria selected in this research
three alternatives. work are: the investment cost, the possibility of expansion,
the availability of acquisition hardware (material acquirement),
Bouhana et al. [14] have proposed a multi-criteria decision- human resources and proximity to market demand. A numeri-
making method based on fuzzy theory, whose goal is to cal example is presented to show the validity of the proposed
minimize, the cost of distribution and the qualitative and model. This example contains three policy makers and three
quantitative criteria which have negative effects on the resi- alternatives.
dents of the city and the environment. The criteria used are
as the following: accessibility, security and connectivity to From the point of view of level of decision, we classify
multimodal transport, cost, environmental impact, proximity to the research work treated the problem in question under
customers, proximity to suppliers, conformance to sustainable uncertain environment according to desired decision. Based on
freight regulations, possibility of expansion, quality of service. the classification of multi-criteria location problems proposed
This methodology has been applied to the case of the public by Farahani et al. [4] presented by figure 3 (Fig 3), we present
authority, which there are three decisions makers and three the research work classified by the table II.
alternatives for location selection.
TABLE II. C LASSIFICATION OF MULTI - CRITERIA LOCATION
Hashim et al. [21] have proposed a multi-objectives SELECTION RESEARCH WORK
decision-making model based on fuzzy theory. This uncertain References Decision
model is converted into a deterministic form by the expected
multi-objectivs multi-attributs
value measure. As a solution, the model gives an approxi-
[8] X X
mate solution. The approximate best solution of the model
[20] X X
is provided using fuzzy simulation. The goal of this model [14] X X
is to minimize the cost (installation cost of the distribution [21] X
center, transport cost from producer to distribution center [22] X X
from distribution center to customers and operational cost of
the distribution center) and maximize clients satisfaction. The
constraints included in the model proposed are as following:
constraints linked to the freight quantity transported from III. D EFINING AND SELECTING LOCATION CRITERIA
the center distribution to customers, to the freight quantity
transported from producer to center distribution, to the capacity In the process of selection it is necessary first and foremost
of center distribution, to number of distribution center to be to identify the set of infuential criteria relevant to the urban
opened, offer and demand. A numerical example is presented distribution centers [8]. Many influential criteria are considered
which there is five potential centers and five client. The authors for the selection of an urban distribution centers location. The
aim to select three among the five centers proposed. They following table (table III) presents the summary of most crite-
have demonstrated that the problem in question is a convex ria in urban distribution centers’ location selection’s problem.
 TABLE III. S UMMARY OF MOST CRITERIA IN URBAN DISTRIBUTION CENTERS ’ LOCATION SELECTION ’ S PROBLEM

Criteria Definition Unit of measurment Criteria type

Accessibility Access by public and private transport Quantitative Benefit
modes to the location
Security Security of the location from accidents Qualitative Benefit
Connectivity to multimodal Connectivity of the urban distribution Quantitative Benefit
transort center with other modes of transport
(highways, railways, seaport, airport,
etc.)
Costs Costs combining land cost, vehicle re- Quantitative Cost
sources cost, policy cost and taxes
Environmental imapact, Impact of the implementation of the Quantitative Cost
UDC on the environment, example (pol-
lution, noise...)
Proximity to customers Distance of location to customer Quantitative Benefit
Proximity to suppliers Distance of location to suppliers Quantitative Benefit
Conformance to sustainable Ability to conform to sustainable freight Qualitative Benefit
freight regulations restriction imposed by public authori-
ties. Example (restricted delivery hours,
special delivery zones, nature and size
of the used vehicle)
Possibility of expansion Capability to augment the size to ac- Quantitative Benefit
commodate increasing demands
Quality of service Ability to assure timely and reliable Qualitative Benefit
service to clients
Natural conditions They mainly include the meteorological Qualitative Benefit
conditions, the terrain conditions, and
the hydrologic conditions
Infrastructure coditions They mainly include the reliability of Qualitative Benefit
the infrastructure and convenience of
communication systems
Resource availability Availability of resources to various uses Quantitative Benefit
Human resource Human resource is the set of individuals Quantitative Benefit
who make up the workforce of an urban
distribution center

This is why there is a growing interest in researches under

uncertainty.
Based on the review paper, as future research, we suggest
a personalization information system. This system to our
knowledge has not yet proposed to solve the problem of
location selection. As a matter of fact, the choice of a location
personalized to install an urban distribution center according
to the needs, preferences and personal profile presents a
challenge. Where, perceptions and personal preferences of
decision-makers exercise, more or less explicitly, a significant
Fig. 3. The classification of multi-criteria location problems [4] influence on more than three-quarters of location selection
[23]. This is due to the complexity and ambiguity of the
decision in a context where the criteria and objectives of the
selection are varied and increasingly specific to each case.
IV. C ONCLUSIONS AND DIRECTIONS FOR FURTHER
Therefore, we plan to use research of Soui et al. [24] in which
RESEARCH
the authors have proposed a multi-criteria decision making
approach for personalization system. This approach aims to
In this paper we reviewed literature of urban distribution
satisfy multiple and contradictory criteria. We plan to use,
centers’ location selection’s problem which has treated under
also, researches of Omri and Chougui [25, 26], in which fuzzy
uncertain environment or certain environment as much as it
concepts and similarity computing were discussed. The main
uses classic methods or hybrid methods. Yet research dealing
objective behind using the proposed similarity measures is to
with this problem in an uncertain environment gave satisfactory
deal with fuzzy parameters like costs combining land cost,
results (urban distribution centers’ location), but these results
distance of location to customer, taxes, etc.
do not reflect the totality of reality. This is due, on the one hand
to the decision level which the desired decision of location se-
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