Abstract
In every-day life, people and goods have to be transported from one place to another by
different kinds of resources, e.g. buses, trains, airplanes and ships, but also transport
belts, cranes, elevators and robots. A group of these resources linked together with the
purpose of transporting people and/or goods from one place to the other forms a logistics
network. Such a network is usually run by a number of logistics providers, some of which
control the links while others control the nodes of that network. Each provider faces the
problem of delivering the right amount of items in the right place at the right time. To
satisfy these goals at minimal costs, a provider has to make combined decisions at three
levels: strategic, tactical and operational.
Due to the ever-growing complexity of the combined decisions, more often a provider
requires efficient decision tools (mathematical models) that solve the problems for him.
During the last decades, the number of people and goods to be transported has grown
that large that even intelligent decision support tools cannot solve the combined decisions
at once. A possible approach is to separate the overall problem into several subproblems,
which are then solved step by step, or if possible alternatingly.
In this dissertation we propose, develop and test multi-step optimization methods to
support logistics providers in their decision making process in two particular logistics networks:
i) a distribution network and ii) a multi-terminal container operation as node in
a network. The separation of the combined problems into several subproblems is chosen
such that each individual subproblem is practically interesting in its own right and can
be solved within the time allowed at the considered decision making level(s). Although
existing theoretical studies have already investigated several parts of the considered logistics
networks, the separations chosen in this dissertation are unique and result from
specific problems faced in practice. The research in this dissertation is supported by the
Koninklijke Frans Maas Groep (taken over by DSV) and the terminal operator PSA HNN
in Antwerp Belgium, who both provided us with interesting, practical problems and data
to test our methods.
The study concerning the distribution network discusses the joint problem at the tactical
and operational level faced by a third party logistics services provider. The objective
is to construct a consistent and efficient network topology (i.e. where to establish line
hauls between suppliers, warehouses and retailers), that still enables just in time delivery
at the operational level. A procedure is proposed that iteratively deletes network line
hauls based on the operational performance of the present topology. An extensive number
of experiments suggest that the proposed alternating procedure is very fast and finds
quite accurate solutions. As expected, the constructed network topology is sensitive to the
averages of supply and demand. Interestingly, the constructed network topology appears
to be robust to changes in second and higher orders of supply and demand distributions.
With respect to the multi-terminal container operation, we consider one terminal operator,
who is responsible for multiple terminals in one container port. The combined
problems at strategic, tactical and operational levels in this multi-terminal container operation
are separated into four main problems. The first subproblem investigates whether
the same number of vessel lines can be operated with a smaller amount of crane capacity
and at the same time the amount of container transport between the different terminals
can be reduced. The proposed approach aims to spread the vessels over the terminals
and over time such that the workload is balanced and the inter-terminal transport is minimized.
Although we guarantee that quay and crane capacities are never exceeded, the
specific berth positions and crane allocations are still to be determined. Results of a case
study in a representative data set suggest that a significant amount of crane capacity can
be saved and at the same time the amount of inter-terminal transport can substantially
be reduced.
Once the various vessel lines have been allocated to a terminal for a certain amount
of time, the second subproblem is to construct a refined schedule per terminal, which
is robust to disturbances on vessel arrivals. In our definition a schedule is robust if for
all arrival scenarios within an arrival window, feasible solutions exist and the maximally
required crane capacity in the worst case scenario is minimal. A window-based model is
proposed that allows slight modifications in the allocations from the first subproblem to
increase the robustness of the terminals’ schedules. Again, we allocate quay and quay
crane capacities, while the specific berth positions and crane allocations are not constructed
yet. As expected, the window-based plan requires slightly more crane capacity
than the nominal window-ignoring plan for zero or relatively small arrival disturbances.
However, the window-based plan is much more robust to larger realistic disturbances that
are still within the arrival window bounds.
Given the schedules, the third subproblem allocates berth positions for the vessel
lines at the quay and stack positions for the containers in the yard. These combined
decisions determine the total travel distance, that has to be covered by straddle carriers
moving containers from quay to yard and vice versa. A procedure is developed that
alternatingly allocates i) berth positions, guaranteeing non-overlapping and ii) container
blocks, ensuring that block capacities are never exceeded, such that the total straddle
carrier distance is minimized. The alternating procedure appears to be very fast, but the
result heavily depends on the initial condition. A second model is proposed that turns
out to find a proper initial guess for the alternating procedure. Results suggest that
the straddle carrier distance in a representative allocation can significantly be reduced by
applying the proposed method. Recently, results of this procedure have been implemented
in a terminal operated by PSA HNN.
The results of the first three subproblems construct tactical schedules, berth positions
and yard design. The fourth subproblem addresses the online operational decision making
if the system is disrupted from this tactical timetable. A rolling horizon approach is
proposed that takes forecasts on arrivals, load compositions and resource activities into
account to construct decisions on the current operations. Subsequently, the vessels’ i)
time allocation, ii) berth position allocation, and iii) crane allocation under disturbances
are addressed. The three subproblems can be solved within the time allowed at this
operational level. Experiments suggest that explicitly taking the forecasts of specific parameters
into account can substantially reduce the operational costs. Hence, we think the
proposed procedure can properly serve as a decision support tool for a terminal operator.
This research clearly shows that the proposed methods can be very valuable for logistics
providers. The actual implementation of one of the results into a terminal operated
by PSA HNN is already a confirmation of the method’s suitability. Although the approaches
in this dissertation may not take all specific managerial decisions into account,
at least we are able to quantify the additional costs induced by these decisions.
Original language | English |
---|---|
Qualification | Doctor of Philosophy |
Awarding Institution |
|
Supervisors/Advisors |
|
Award date | 19 Mar 2009 |
Place of Publication | Eindhoven |
Publisher | |
Print ISBNs | 978-90-386-1572-1 |
DOIs | |
Publication status | Published - 2009 |