Journal of Service Science and Management, 2011, 4, 174-183
doi:10.4236/jssm.2011.42021 Published Online June 2011 (http://www.SciRP.org/journal/jssm)
Integrated Logistics Network for the Supply Chain
of Locally Produced Food, Part I: Location and
Route Optimization Analyses
Techane Bosona, Girma Gebresenbet, Ingrid Nordmark, David Ljungberg
Department of Energy and Technology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Received March 14th, 2011; revised May 3rd, 2011; accepted May 7th, 2011.
ABSTRACT
Due to a growing interest in locally produced food (LPF), there is a tendency of promoting local food systems. The ob-
jective of this study was to investigate the existing flow of LPF from producers to consumers and develop a coordinated
and efficient distribution system for producers in Halland region, Sweden. An integrated logistics network (ILN) em-
bracing producers, retailers, a collection centre (CC) and a distribution centre (DC) was proposed. Data collection,
location analysis and route optimization analysis were conducted. Geographic information system (GIS) and Route
LogiX software were utilized for the analyses. Four scenarios of food distribution were identified and analyzed. When
compared to the existing system, the best scenario improved transport distance, time and number of routes up to 93%,
92% and 87% respectively. The distribution of LPF was integrated into large scale food distribution channel (LSFDC)
and this could increase the sustainability of local food system.
Keywords: Locally Produced Food, Location Analysis, Route Optimization, Collection Centre, Distribution Centre
1. Introduction
The globalizations of industries and low prices in trans-
port sector have increased the distance between the place
of production of goods and the consumer [1]. In the ag-
riculture sector, globalization of food production has
considerably affected the food supply system by increas-
ing tonne-kilometers, increasing emissions of greenhouse
gases and disconnecting local food producers and con-
sumers [2]. Since this disconnection adversely affects
smaller producers, their environment, societies and cul-
ture, there is a tendency of reconnecting local food pro-
ducers and consumers.
The growing interest in LPF [1,3-5] has relation with
increased environmental and food quality issues and at-
tracted many consumers and researchers. The existing
studies on the benefits and impacts of LPF are partial and
few in number. Therefore, more studies are required in
order to draw conclusions about economical, social and
environmental benefits of the local food system and to
assess the possible constraints [3].
Although there is no generally agreed definition [3],
LPF can be characterized by the proximity of produ ction
place to the consumers [5]. In terms of distance, usually
there is a limit, e.g. 160 km in UK [1,3] and 250 km in
Sweden [1]. In addition to geographical distance, LPF is
also con sidered as food which meets a number of criteria
such as animal welfare, employment, fair trading rela-
tions, producer profitability, health, cultural and envi-
ronmental issues [3]. In the current study, LPF refers to
food produced and consumed mostly within particular
geographical area and also distributed within the country.
There are many advantages associated with local food
system. The main advantages [1,2,6] are:
 Economic advantages: it supplies products that have
more values such as freshness, high quality and safety; it
increases direct sale to consumers and strengthens the
local economy.
 Social advantages: It increases employment oppor-
tunities in rural regions, enhances the local tourism, and
promotes community integration.
 Environmental advantages: It reduces transport dis-
tance which in turn reduces emissions, and it minimizes
the use of packaging materials.
However, there are also constraints associated with
*This study is sponsored by the Swedish Board of Agriculture and
Vinnova research and innovation for sustainable growth.

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
Analyses
175
local food production. The production can be more la-
bour intensive which might increase the cost to the con-
sumer, running and maintenance can be more expensive
and transportation can be energy inefficient [1]. But, the
producers can work together (through producers’ net-
work) and be cost effective by sharing resources and co-
operating in marketing schemes [1].
Due to the increased demand for LPF, there is an in-
terest to raise the profile of LPF and bring farmers and
consumers closer together [7]. This is underway by en-
couraging the purchase of LPF and developing systems
for marketing, distributing and selling LPF. In Sweden
farm shops and farmers’ markets have been ways to local
food market promoting social interaction of local food
producers with the consumers and their fellow producers
while the consumers are willing to support the local pro-
ducers by buying their products [1]. But there is also
negative aspect of farmers’ market. For example a case
study in Sweden indicated that half of the people attend-
ing the farmers’ markets drive their own cars leading to
more congestion and greenhouse gas emission [1]. Inef-
ficient logistics activities, fragmented communication
messages and lack of resources to effectively provide
information about food and farming to consumers are the
main problems noticed in the case of local food systems
[7]. This indicates the need of a coordinated distribution
of LPF using an integrated approach.
Although collaboration improves logistics performance
[8-11] effective logistics collaboration in the food
delivery system can be possible through integrated
logistics network (ILN). A network of food suppliers has a
collective responsibility to supply food through managing
flows of food products and providing information about
the food products and relevant features of food supply
such as food quality and origin [12]. Although, the need
for food product traceability is becoming increasingly a
global issue, developing food product traceability systems
has been a m a jor c hall enge b ot h tec hni cally a nd ec onomi-
cally [2,12] . Inform ation connectivi ty is aspect of network
integration that creates foundation for tracing products
[12]. In such a network, optimally located and centralized
warehousing and efficient management of logistics
services as well as consolidation of goods are essential
[8,13]. For this purpose location analysis and route
optimization analysis are required.
Optimizing the location of distribution centers or hubs
improves the efficiencies of transportation system, and it
has the dynamic implication over time [13]. Since a hub
system reduces cost, distance and time by avoiding direct
routing between all origin-destination pairs, in the facil-
ity (e.g. CC) location analysis, costs and distances are
important quantitative attributes to be considered. Some
other attributes that influence the location decision [13,
14] are: 1) access to production point, markets and/or
distribution centers; 2) potential development of the re-
gion; 3) availability of labour and professional staff; 4)
availability of transportation facilities; 5) availability,
quality, and price of utilities and services; 6) govern-
mental considerations; 7) environmental and ecological
considerations; and 8) cost, size, zoning, and topography
of available land.
Route optimization analysis is an important means to
create improved goods distribution systems. It has been
used in different areas, such as forest harvesting [15],
solid waste collection [16] and agricultural goods trans-
port [17], to reduce operational costs, and emissions.
In the existing situation, the producers transport their
products directly to their customers. Such uncoordinated
distribution system is not efficient. In addition to this,
there are other barriers that reduce the sales of producers,
e.g. most consu mers want to bu y all the food in one place
[18], the quantity and price of LPF fluctuates seasonally,
the supply size and quality of products are limited in
some cases [5,19]. This makes it difficult for a single
farmer or smaller shop (especially in big cities) to com-
pete with the big retail chains [5].
In order to solve these problems, new and better form of
food distri bution is required [10]. One of the po ssible new
alternatives is integrating the logistics activities via hub
network [20] enabling the formation of local food distri-
bution lines that o perate in conjunction with, or within , a
larger conventional food business [5,21]. In this study, it
was intended to study this innovative concept in depth
with practical application in Halland region. For this
purpose, ILN that connects producers, retailers, CC, and
DC was formed to efficiently coordinate the logistics
activities through integrated approach, where the distri-
bution of products from producers is to be coordinated
through CC and DC and supported with information
technology (IT) system as shown in Figure 1.
The main objective o f this study was to investigate the
existing flow of food products from producers to con-
sumers and to develop a coordinated and efficient food
distribution system for local food producers participating
in this pilot project in Halland region, Sweden. The spe-
cific objectives were to:
1) collect relevant data and organise in data analyzing
tools such as GIS and Route LogiX software;
2) map the producers and delivery points (retail-
ers/customers);
3) determine the optimum location of CC and DC;
4) carry out route optimization analysis;
5) integrate the distribution of locally produced food
into the large scale food distribution centre.
In summary, there is a tendency of reconnecting local
food producers and consumers due to the growing inter-

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
Analyses
176
Figure 1. The concept of integrated logistics network in
Halland project.
est in LPF. In the existing situation, the distribution of
LPF is uncoordinated and not efficient. Therefore, form-
ing ILN and planning optimized delivery routes for LPF
are essential to promote efficient and effective logistics
services for small scale food producers and improve the
sustainability of local food supply system in the Halland
region. The ILN is useful to solve the problems related to
logistics, access to larger market, and access to informa-
tion on the origin and quality of the food products. The
results of this study confirmed this. The findings indi-
cated that the implementation of ILN, in the delivery
system of LPF, could reduce the transport distance, time
and number of routes (number of vehicles) very signifi-
cantly.
This paper is structured as follows. In Section 2, the
materials and methods are described. In Section 3, the
results are presented. In Section 4, the findings have been
discussed. And in Section 5, the major conclusions and
recommendations for future research have been given.
2. Materials and Methods
2.1. Project Area, Producers and Delivery Points
The project area is located in Halland County which is
situated between 56˚19'07"N and 57˚35'56"N latitude
and 11˚27'37"E and13˚42'08"E longitude (see Figure 2).
There were 14 producers considered in this study and all
of them are located in Halland County. For four of them,
only their addresses and annual production quantities
were available. The remaining ten producers had infor-
mation including the addresses of their respective deliv-
ery points. There were 44 (see Table 1) delivery points
(addresses of existing customers) and most of them are
located in Västra Götland, Halland and Skåne counties
(see Figure 2).
Figure 2. Map of south Sweden, illustrating locations of
producers, delivery points, CC and DC.
2.2. Data Collection
Data was collected through question n aires and interviews.
The questionnaire was structured and sent to all produc-
ers. The collected data consisted of producer and cus-
tomer addresses, frequency of delivery, annual produc-
tion quantity, type of products, annual revenue, distribu-
tion cost as percentage of revenues and additional infor-
mation on product distribution. Some of these data (e.g.
annual revenue and distribution cost) are to be analyzed
and reported in the part II of this paper.
2.3. Location Analysis
2.3.1. Optimum Location of Food Collection Center
Two methods were employed to determine the best loca-
tion of the CC. The first method was Centre-of-Gravity
technique and the second method was Load-Distance
technique. The mathematical equations of these tech-
niques have been described by [22]. The techniques op-
timize the location of a facility such as CC by minimiz-
ing the transport distance and transport time, leading to
economical and environmental benefits.
In the first method, the optimum location of CC was
determined using the distance goods transported and
weight of the delivered products [22]. The method uses
straight line distances (between producer and CC) based
on the coordinates of each producer and CC, on the digi-
tal map. The coordinates of the 14 producers, in relation
to that of CC, and their annual produ ction quan tities were
used in this analysis.
The second method is used when different options of
locations are suggested, and the product of load and dis-
tance is used as measuring value. In the current case,
three locations were suggested, and load-distance meas-
uring value was determined for each. Finally, the loca-

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
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177
Table 1. Producers, their production quantity and number of delivery points.
Producers
Description P1 P2 P3 P4P5P6P7P8P9P10P11 P12 P13 P14
Quantity[t year-1] 20 55 25 15015168965303065 30 60 50
No. of delivery points 7 6 3 5 2 2 5 5 4 5 no info* no info no info no info
*-no information on number of delivery points was obtained
tion with lowest value of the summation of the load- dis-
tance value was selected. The actual road distances were
calculated with Route LogiX software [23] and the an-
nual production quantity was considered as load value.
One of large scale food distribution centers found in
the region of these producers was chosen to serve as DC
for the LPF. This DC is located in Helsingborg city and
owned by one of the LSFDCs in Sweden. From the CC,
the LPF are to be transported to distribution centre (DC).
2.3.2. Mapping the Production and Delivery Points,
CC and DC
First, the longitude and latitude coordinates were deter-
mined for each producer, delivery point, and DC based
on their postcode and additional geographical informa-
tion obtained from digital database. The coordinates of
CC were determined as described above. Then all the
identified locations were mapped using ArcMAP of GIS
software [24]. A point shape files representing the geo-
graphic location of these places were created and dis-
played on the map (see Figure 2).
2.4. Scenarios for Collection and Distribution of
Locally Produced Food
Coordination wi t hi n foo d s u ppl y chai ns i s essent i a l for t he
effectiveness and efficiency of chains in the competitive
environment and coordinative structures can be organised
in different ways [25]. In the current study, different
scenarios were considered to realize such coordination. In
the coordination process different routes were created
using the digital maps which enable the visualization of the
production and delivery points in relation to CC and DC.
The route optimization analysis was carried out using
RoutelogiX software which has most powerful vehicle
routing including optimization [23]. It finds optimized
routes by minimizing driving distance and time, which in
turn reduces transport cost and emission of green house
gases. Since this software handles planning of one vehicle
at a time, each of the routes formed in this study was
optimized separat el y [23].
For detailed analysis, four scenarios were set carefully
taking into consideration the relations between the pro-
ducers, the delivery points, CC and DC. The delivery
frequency and quantity p er tour were also taken into con-
sideration based on the available information.
2.4.1. Scenario 1: When Producers Distribute Their
Products
In this case, all producers deliver their produces to their
respective customers (retailers) in a single or more routes
depending on the location and number of their custom-
ers/delivery points (see Figure 3). This scenario is simi-
lar to current distribution practice. Since there is no detail
information concerning the distribution route for each
producer (only the locations of customers were available)
product delivery route was created for each producer
with the assumption that deliveries to customers which
are very close to each other can be done by the same
route. Totally 23 possible routes were formed and ana-
lyzed under this scenario.
2.4.2. Scenario 2: Collection by Producers and
Distribution by DC
Scenario 2 includes three parts of transporting products
from producers to retailers. These are transporting from
producers to CC, from CC to DC and from DC to deliv-
ery points (see Figure 4). Under this Scenario two op-
tions, Option I and Option II, were considered.
Option I: Wh en distribution o f food products fr om DC
to retailers is to be treated separately at DC i.e. assigning
vehicles that distribute only LPF of the producers under
consideration. For this purpose, 5 distribution routes
were designed where the number of delivery points
served by a single route varied from 2 to 12.
Option II: An Integrated distribution: In this case,
transporting LPF from producers to CC and from CC to
DC is similar to that of Option I. However, the delivery
from DC to delivery points was considered to be inte-
grated into the existing distribution routes of LSFDC. It
was also assumed that the products could be delivered
only by utilizing the empty space of the trucks in the
LSFDC as about 30 - 40% of loading capacity of these
Figure 3. Fragmented distri bution in Sc e nario 1.

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
Analyses
178
Figure 4. Uncoordinated collection and coordinated distri-
bution for Scenario 2 (Option I).
trucks is usually unutilized.
2.4.3. Scenario 3: Collection by CC and Distribution
by DC
In Scenario 3, the collection of products to CC and de-
livery to DC were considered to be coordinated and man-
aged by the CC and for this two routes were created (see
Figure 5). Similar to scenario 2, in scenario 3, two op-
tions were considered for distribution from DC to con-
sumers/retailers.
2.4.4. Scenario 4: Integrated Collection and
Distribution
In Scenario 4, both collection and distribution of prod-
ucts were to be coordinated in every route. This coordi-
nation is to be performed by centralised management
with support of IT system, where the drivers receive in-
formation from the communication centre and collect the
products from the producers while delivering to the re-
tailers at the same time (see Figure 6). This can be prac-
tical by furnishing the trucks with different compart-
ments for different products being collected and deliv-
ered. In this case, the task is to pick the products from
producers in a route and deliver to the retailer in the same
route. Four routes were created based on the geographical
Figure 5. Coordinated collection and coordinated distribu-
tion for Scenario 3 (Option I).
Figure 6. The concept of coordinated collection and distri-
bution (scenario 4).
location of producers and delivery points i.e. assigning
producers and consumers close to each other, on the
same route.
Concerning the vehicles, in scenario 1 (existing system)
and in the collection part of scenario 2, the producers
could use light transport cars and passenger cars. In the
option I (of scenar io 2 and scenario 3) and in scenario4 it
was assumed that light trucks with loading capacity up
to 3.5 t would be assigned. In option II (of scenario 2 and
scenario 3) it was assumed that light trucks (for collec-
tion and transporting to DC) and heavy trucks (about 30 -
40% of the capacity of trucks owned by LSFDC) would
be used for further distribution from DC.
3. Results
3.1. Investigation of Producers and Product
Delivery Points
All the producers of LPF considered in this study were
located within the radius of 50km from CC, within
Halland County (see Figure 2) while most of their exist-
ing customers were found within the radius of 180km
from CC. Out of 44 delivery points, 22 were found in
Halland (50%) and 20 delivery points were located in the
adjoining counties (46%). Only 2 d elivery points were in
non adjoining counties.
Two of these delivery points, Norrtälje (within Stock-
holm County) and Eskilstuna (within Södermanland
County) are far from both CC and DC (see Figure 2).
Norrtälje is the furthest away, 625 km from DC and 554
km from CC while Eskilstuna is the second furthest away,
520 km from DC and 443 km from CC. Delivery to
Norrtälje was only once per week, while delivery to
Eskilstuna was 5 times per week.
Table 1 reports the number of delivery points for 10 of
the producers and the number varied from 2 to 7. Totally,

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
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179
the 14 producers produce 700 tons per year. For each
producer th e quantity varied from 15 tons to 150 ton s per
year with mean value of 50 tons per year.
The largest product type was fruits and vegetables as
about 33% of the producers supplied fruits and vegeta-
bles. About 25% supplied meat while the grain products,
egg and dairy products were supplied by 17%, 17% and
8% of producers respectively. The producers were selling
about 63% of the products within their own county (see
part II). The producers used three means to transport
their product to customers in the existing distribution
practice (see Figure 7), i.e. using their own vehicles
(75%), working with transport companies (68%) and
cooperating with other producers (16%) (see Figure 7).
3.2. Location and Route Optimization Analyses
The location analyses conducted using Centre-of-Gravity
and Load-Distance techniques showed that the optimum
location of the CC was at place called Slöinge with coor-
dinates of 56˚ 55'15"N latitude and 12˚34'15"E longitude.
The geographical location of the DC was at 56˚02'56"N
latitude and 12˚43'08"E longitude which is located in
Helsingborg city , about 2 08 k m away from CC.
Regarding the route optimization analysis, 23 routes
were created and analyzed in scenario 1. The results in-
dicated that the simulated driving distances and times
varied from 56 km to 1554 km and from 57 min to 17 hr
respectively. For the scenario 1, total driving distance
was 6159 km while total driving time was about 69 hr.
In scenario 2, the driving distance and time were simu-
lated for each producer in the case of food collection to
CC. For two producers, the driving distance and time
were considered to be zero, because they were located at
the same place as CC. For the rest of producers, the
simulated driving distance varied from 9 km to 123 km
while the driving time varied from 6 min to 1 hr and 36
min. The total distance and time for the 10 producers
were 519 km and 6 hr and 26 min.
For scenario 3, two optimized collection routes were
Figure 7. Means of transporting LPF in the current practice.
formed and analyzed. The simulated driving distances
were 70 km and 169 km for route1 and route 2 respec-
tively while their driving times were 1hr and 2 hr and 33
min. For the case of food distribution from DC to cus-
tomers/retailers, 5 routes were formed and optimized in
both scenario 2 and scenario 3. The total driving distance
and time for the 5 routes were about 3047 km and 34 hr.
The distance of each route varied from 425 km to 1352
km while the time varied from 1 hr and 27 min to 14 hr.
Considering both collection and distribution routes to-
gether, for scenario 2 (option I), total simulated driving
distance and driving time of all routes were about 3774
km and 42 hr respectively. For option II the figures
were less i.e. about 727 km and 8 hr. Similarly, for sce-
nario 3 the total driving distance and time were about
3493 km and 40 hr for Option I , and about 446 km and 6
hr for option II. Figure 8 presents examples of simulated
routes in scenario 3.
For the scenario 4, the simulated driving distance and
time varied from 133 km to 1124 km and from 3 hr to 13
hr. The total driving distance and time and number of
routes were 2343 km, 30 hr and 4 routes respectively
indicating the improvements of 62%, 57% and 83% (see
Table 2).
Table 2 presents the summary of route optimisation
analysis for all scenarios . Wh en compa r ed to s c e nar io 1 , a
significant saving was gained in distance, time and no of
routes in the remaining three scenarios. For example, in
scenario 2 (option II) the driving distance, driving time
and n o o f ro ut es we re re du ce d fr om 61 59 km , 69 h r a nd 2 3
routes to 727 km, 8 hr and 11 routes respectively, indi-
cating improvement of 88% in both distance and time
and 48% in no of routes. Similarly, in option II of scenario
3, the total driving distance and time and no of routes
were 446 km, 6 hr, and 3 routes with respective im-
Figure 8. Examples of simulated routes for Scenario 3. (a)
Collection route, (b) Distribution route.

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
Analyses
180
Table 2. Summary of route optimization analysis.
Scenario Driving
Distance Driving Time No. of routesImprovement when compared to Scenario 1[%]
[km] [h] Distance Time no. of routes
Scenario 1 6159 69 23 - - -
Scenario 2
Option I 3774 42 16 39 39 30
Option II 727 8 11 88 88 48
Scenario 3
Option I 3493 40 8 43 42 65
OptionII 446 6 3 93 91 87
Scenario 4 2343 30 4 62 57 83
provement of 93%, 91% and 87%.
Table 2 presents the summary of route optimization
analysis for all scenarios. When compared to scenario 1,
a significant saving was gained in distance, time and no
of routes in the remaining three scenarios. For example,
in scenario 2 (option II) the driving distance, driving time
and no of routes were reduced from 6159 km, 69 hr and
23 routes to 727 km, 8 hr and 11 routes respectively, in-
dicating improvement of 88% in both distance and time
and 48% in no of routes. Similarly, in option II of sce-
nario 3, the total driving distance and time and no of
routes were 446 km, 6 hr, and 3 routes with respective
improvement of 93%, 91% and 87%.
4. Discussion
4.1. Main Characteristics of Existing Local Food
Delivery System
More than one third of producers produce fruits and
vegetables. The physical distribution of such products
requires appropriate packaging in order to be transported
to end users. This type of pack aging can be facilitated by
the proposed ILN.
Concerning the food distribution activities, collabora-
tion in the food supply chain was relatively uncommon in
the existing system. Only about 16% of the participants
had collaboration with othe r pr oducers so far. Although it
was at low level, such an experience of collaboration can
play important role in implementing the proposed coor-
dinated distribution system in the Halland region. It was
also known that about 68% of participants had experi-
ence of working with transport companies. Most of the
participants (about 75%) transported their products
mainly with their own vehicles indicating that the logis-
tics activities in the existing local food system were un-
coordinated and needs improvement.
In the existing system, the frequencies of product de-
livery to customers varied markedly. Some of the pro-
ducers delivered ten times a week to its major customers,
while others only delivered during a limited period of the
year and/or every other week. This has great impact on
the logistics, because it makes the transport demand vary
considerably throughou t the year.
4.2. Location and Route Optimization Analyses
The location analysis enabled determines the best loca-
tion of CC which facilitated the coordination of product
collection and delivery to DC. This CC was determined
considering only limited number of producers and their
production quan tity. If more producers jo in the system in
the future or if the producers increase production quan-
tity the location of optimum CC might change.
The result of rout optimization analysis indicated that
the ILN could reduce the transport distance, time and
number of routes when compared to the current distribu-
tion practices which is similar to scenario 1. Although
the improvements were gained in both option I and op-
tion II (in scenario 2 and scenario 3), more saving was
gained in option II, especially the saving in distance and
time was increased by more than 50% when compared to
the saving in option I. The saving in scenario 4 was bet-
ter than that of option I.
Option II of scenario 3, in which the improvements of
93%, 92% and 87% were gained for distance, time and
routes respectively, was found to be the best of all sce-
narios followed by option II of scenario 2. This signifi-
cant saving in the option II was the result of integrating
the distribution of LPF into the conventional LSFDC.
4.3. Implications of ILN
4.3.1. Improving Logistics Service
In the existing product delivery system, about 75% of
producers use their own vehicles to transport their prod-
ucts i.e. the logistics service is fragmented. The produc-
ers expressed their ambition to solve logistics problems
through the application of the proposed ILN. Previous
studies [26] and the significant improvements obtained in

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
Analyses
181
the current study indicated that the integrated approach
could increase the efficiency of logistics service in the
supply chain of LPF. In the indentified scenarios, espe-
cially, in the option II of scenario 2 and scenario 3, the
LPF were considered to be loaded on empty spaces of the
trucks being used in the conventional LSFDCs and this
greatly improved the efficiency of utilizing the vehicles
loading capacity. However, in option II, the delivery
frequency and quantity to each existing customers might
change leading to the dissatisfaction of these customers
and this should be investigated further.
4.3.2. Expandi ng Po tential Market Area
In this study, in addition to finding better solu tion for the
logistics problems, the objective of the producers was to
expand their sales area. Only 2 out of 44 existing cus-
tomers were in non adjoining counties indicatin g that the
producers have difficulties to expand their sales area and
reach the consumers in the other counties.
However, increasing sales of LPF needs to overcome
the main problems (related to local food syste ms) such as
low size of production and more volatility of market
price and high seasonality of food products on market
[4], inadequate or no packing and storage facilities,
limited or no means of transport and limited knowledge
of potential market [5]. These problems can be over-
come, if the LPF be embraced by dominant food super-
market and superstore chains [3] and this can be facilitated
by the application of the proposed ILN which integrates
the local food system into LSFDC and fulfils the ambition
of the producers to expand their sales.
4.3.3. Improving Access to Information
Efficient ways of sharing information and scarce/
exp e ns i ve re s ou rc es pl ay a k e y ro l e in d e ve lo pi n g IL N [ 27 ,
28]. Well organized information concerning local food is
also important to satisfy the increasing demand of con-
sumers to have good knowledge and information of the
food origin and how it is handled and transported [29].
Such consistent flow of information in local food system
could be realized via the application of this ILN enabling
producers and consumers get access to the right informa-
tion at the right time.
4.3.4. Improving the Sustainability of Local Food
Systems
The de vel ope d IL N i s im p o r tan t to s e cu r e t h e f lo w o f LPF
from producers to consumers and to improve the food
quality through training opportunities and sharing/ learn-
ing professional skills [1]. This type of better fo od supply
chain management that empowers the producers is re-
quired to achieve sustainable local food supply chain
[25,30]. Especially in European countries where the
populations mostly use supermarkets, local food system
can be sustainable if it can become financially and
physically accessible to the mainstream market, maxi-
mizing distribution of LPF through supermarkets [21]
and this accessibility to large market can be achieved
through the app lication of the proposed ILN.
The positive implication of ILN towards achieving and
maintaining more sustainable local food systems can be
confirmed by expanded potential markets, access to bet-
ter technologies and practices, improved logistics and
minimized food miles and reduced green house gas
emissions [17,31], traceability of food origin, availability
of information on nutrition and value. This ILN also cre-
ates more opportunity for identifying problems in the
supply chain of LPF and launching research projects to
provide appropriate solutions and maintain the sustain-
ability of local food systems in different regions/
countries [4].
Part II of this paper reports the results of analyses done
regarding the implications of the proposed integrated
approach on environment, marketing arrangements/
managements and economic tradeoffs in the supp ly chai n
of LPF.
5. Conclusions
This study initiated with the aim to investigate the exist-
ing flow of LPF from producers to consumers and to
develop a coordinated and efficient food distribution
system for local food producers in Halland region. For
this purpose, an ILN that embraced fourteen producers,
44 delivery points, one CC and one DC was formed. All
producers were located within the radius of 50km from
CC. Most of their existing customers were found within
Halland county (50%) and the adjoining county (46%)
within the radius of 180 km from CC.
The optimized CC was located at 56˚55'15"N latitude
and 12˚34'15"E longitudes. The DC, which was 208 km
far from CC, was used as centre of the network to inte-
grate the local food system into LSFDCs.
The formation of ILN and the location and route opti-
misation analyses, conducted based on four scenarios
utilising tools such as GIS and professional Route LogiX
software, made it possible to get more insight into the
impact of integration of local food systems. When com-
pared to the existing, uncoordinated delivery system
which was most similar to scenario 1, the remaining sce-
narios (scenarios 2, 3 and 4) showed significant im-
provements. Option II of scenario 3 was found to be the
best scenario with the improv ements of 93% for tr an sport
distance, 92% for transport time and 87% for number of
routes. Option II also improved the efficiency of utilizing
the vehicles loading capacity in the LSFDC.

Integrated Logistics Network for the Supply Chain of Locally Produced Food, Part I: Location and Route Optimization
Analyses
182
The application of this ILN will satisfy the needs of
producers and consumers through solving the problems
related to logistics, access to larger market, and access to
information on the origin and quality of the food prod-
ucts. These advantages of ILN indicate that the applica-
tion of this type of integration will greatly improve the
sustainability of local food systems.
This study was site specific, and the analysis results
mainly reflect the situation of the supply chain of LPF in
the Halland region, which was selected for this study.
Therefore, similar, site specific and detailed studies are
required to establish well coordinated and sustainable
supply chain systems for LPF.
6. Acknowledgements
The authors would lik e to than k Prof . Dietrich von Ro sen
for his fruitful discussions and valuable suggestions dur-
ing the development of this paper.
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