Semantic transportation planning for food products supply chain ecosystem within difficult geographic zones

Publication Date16 Oct 2017
DOIhttps://doi.org/10.1108/IMDS-10-2016-0459
Pages2064-2084
AuthorMuhammad Ali Memon,Mohamed Hedi Karray,Agnès Letouzey,Bernard Archimède
SubjectInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Semantic transportation planning
for food products supply chain
ecosystem within difficult
geographic zones
Muhammad Ali Memon
Institute of Information and Communication Technology, University of Sindh,
Jamshoro, Pakistan
Mohamed Hedi Karray and Agnès Letouzey
Laboratory Production Engineering, Ecole Nationale dIngenieurs de Tarbes,
Tarbes, France, and
Bernard Archimède
Ecole Nationale dIngenieurs de Tarbes, Tarbes, France
Abstract
Purpose In difficult geographical zones (mountain, intra-citiesareas,etc.),manyshippers,fromsmalland
medium enterprises to individuals, may demand delivery of different food products ( fresh, refrigerated, frozen, etc.)
in small quantities. On the other side, carrier companies wish to use their vehicles optimally. Taking into account the
perishability constraints (short-shelflife, temperature limits, etc.) of the transported food products and environmental
constraints (pollution, carbon impact) while consolidating multiple kinds of food products to use vehicles optimally is
not achieved by current transportation planning solutions. The purpose of this paper is to present an interoperable
solution of a marketplace, formed by shippers and carriers, dedicated to the schedule of food transport orders.
Design/methodology/approach This transportation planning system named Interoperable-Pathfinder,
Order, Vehicle, Environment and Supervisor (I-POVES) is an interoperable multi-agent system, based on the
SCEP (supervisor, customer, environment and producer) model (Archimede and Coudert, 2001). Ontologies
are developed to create the planning marketplace comprising demands and offers from different sources
(multiple shippers and carriers).
Findings A hierarchy ontology for food products. A transporter system ontology. A global ontology that
contains all shared concepts used by local ontologies of both shippers and carriers. I-POVES an interoperable
model, which facilitates collaboration between carriers and their shippers through its active agents.
Practical implications I-POVES is tested on a case study from the TECCAS Poctefa project, comprising
transport and food companies from both sides of the Pyrenees (France and Spain).
Originality/value There has been much work in the literature on the deliveryof products, but very few on
the delivery of food products. Work related to delivery of food products focuses mostly on timely delivery for
avoiding its wastage. In this paper, constraints related to food products and to environment (pollution and
carbon impact) of transport resources are taken into account while planning the delivery.
Keywords Ontology, Interoperability, Food perishability constraints, Multi-agents systems,
Transportation planning
Paper type Research paper
1. Introduction
In the transportation domain, distribution of large volumes is receiving greater attention
(Ulku, 2012). Many efforts are being made for proposing solutions of transportation
displacements concerning distribution to faraway locations in large quantities, and food
Industrial Management & Data
Systems
Vol. 117 No. 9, 2017
pp. 2064-2084
Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-10-2016-0459
Received 31 October 2016
Revised 29 December 2016
14 February 2017
Accepted 13 March 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
© Muhammad Ali Memon, Mohamed Hedi Karray, Agnès Letouzey and Bernard Archimède. Published
by Emerald Publishing Limited. This article is published under the Creative Commons Attribution
(CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article
(for both commercial & non-commercial purposes), subject to full attribution to the original publication and
authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
2064
IMDS
117,9
products are not an exception (Hallman et al., 2015). Bringing food products from distinct
regions across the countries and continents has become a regular routine in todays time.
Consumers find products not grown or produced locally but brought in from distinct areas,
making food business a global phenomenon.
Several solutions are developed and used efficiently by big distributor companies to
bring food products in large quantities, using the capacity of large vehicles
optimally (Chopra and Meindl, 2007). But when it comes to intra-cities transportation,
or more generally geographically difficult zones, many small and medium enterprises
locatedinthesezonesdemanddeliveryinsmall quantities. Thus, food products are
delivered in large quantities at the distribution centers located on the outskirts but
close to these zones, from where they are transported in smaller quantities to the
customers situated within those zones and vice versa. Big vehicles do not enter in these
zones, they unload the products at the distribution center located at the beginning of city
premises, from where products are delivered by small vehicles in small quantities
(Caenegem et al., 2015). Such distribution is called as hub-and-spoke distribution
(Bryan and OKelly, 1999).
The problem of using transport resources optimally in these zones becomes a crucial
issue, because vehicle should not be loaded with less number of products than its full
capacity (less than truckload (LTL) distribution) (Ulku, 2012; Hübner et al., 2016).
Many small product delivery orders need to be shared (order sharing) or grouped for
delivery (capacity sharing) in order to minimize the number of travelings, cost and
especially environmental pollution (Yao and Song, 2013). This problem worsens when the
transport orders concern perishable products.
However, in contrast to other products, food products, due to their perishability, bring
more distribution constraints as weather conditions, tight schedule, short-shelflife, etc.
(Wagner and Meyr, 2015). Due to that, food products can be categorized into different kinds
like frozen, refrigerated, fresh, etc. with their respective constraints and different
temperature requirements.
Therefore, transportation planning must take into account both foods perishability and
vehicles capacity with its temperature maintaining limits in order to consolidate orders.
Transports are realized by specialized transport companies commonly known as third-party
logistics (3PL) (Marasco, 2008; Mehmann et al., 2016) offering delivery services to their
clients. These carriers may propose to deliver the order of same client, forming a competitive
environment. They also require to collaborate with other carriers in order to deliver the
products outside their limited operational territory.
In this context, both shippers and carriers together form a collaborative environment,
which can be called a marketplace for transport services. Forming this marketplace involves
a good understanding of information exchanged between shippers and carriers and between
various carriers, especially about locations, food product constraints (short-shelflife),
transport resource type (vehicle, train, plane), etc. Every entity in the marketplace has its
own management system and standards. Hence, an interoperable mechanism is required to
understand and transform heterogeneous information between these systems and achieve
the collaboration.
This paper presents a solution of a transport marketplace to realize the schedules of
transports for the delivery of food products achieved by the collaboration of heterogeneous
shippers and carriers systems in difficult geographical zones.
In Section 2, the state of the art related to collaborative transportation planning is
discussed. The adequacy of the SCEP (supervisor, customer, environment and producer)
model for transportation is presented in Section 3. Section 4 details the proposed extension
of the SCEP model named Interoperable-Pathfinder, Order, Vehicle, Environment and
Supervisor (I-POVES). Section 5 is dedicated to the application of I-POVES on a case study
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Food products
supply chain
ecosystem

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