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themselves and try to harmonize their plans with those of other coalition part-
ners by applying appropriate request exchange mechanisms. The specific goal of
CTP is to find a reallocation of requests among the coalition members with total
costs smaller than the sum of the forwarders' individual fulfillment costs, i.e.,
without cooperation with other members. The obtained cost-savings present the
joint benefits of the coalition that cannot be achieved individually. These joint
benefits are then to be shared by the members in such a way that all freight
carriers will benefit from the cooperation.
CTP has been investigated by many researchers in the last decade. However,
most of their research on CTP considers only the static planning scenario, where
all information is available a priori at the time CTP is performed. On the con-
trary, little attention has been paid to dynamic CTP problems (DCTPP). In this
paper, a DCTPP with deterministic information in which full truckload (FTL)
pickup and delivery transportation requests are to be served is investigated. In
order to solve the DCTPP, the route-based request exchange mechanism pro-
posed in [31] for the static CTP problem is embedded into a rolling horizon
planning framework. Using computer simulation, the potential of cost-savings
through CTP and the influence of varying degrees of dynamism of instances on
the planning results are analyzed.
This paper is organized as follows. In Section 2, we give a brief literature
review on related topics. In Section 3, the DCTPP is formally described. In
Section 4, the rolling horizon planning solution framework for the DCTPP is
proposed. Computational study and a comprehensive discussion on the results
are shown in Section 5. Section 6 concludes this paper.
2 Literature Review
The DCTPP extends the static CTP problem over a long planning horizon with
gradually revealed request information. The two closely related topics of this
problem are the dynamic and deterministic vehicle routing and the CTP. In this
section, literature reviews on these two related topics are given.
2.1 Dynamic and Deterministic Vehicle Routing
In contrast to static routing problems where all input data are known a priori
at the time when the routes are constructed, some input data are revealed or
updated during the period of time in which operations take place in a dynamic
routing problem [2]. Moreover, a routing problem can be either deterministic
or stochastic according to the information quality which reflects possible uncer-
tainty on the available data [20]. The reader is referred to [20] for a recent review
on dynamic routing problems. Specifically, [2] review the literature on dynamic
pickup and delivery problems (PDP). In this section, we focus on some major
contributions to dynamic and deterministic routing problems.
The solution approaches for dynamic routing problems can be classified ac-
cording to [20] into two categories. The first one comprehends periodic re-
optimization approaches. After having constructed a set of initial routes, these
