Multi-step optimization of logistics networks:strategic, tactical, and operational decisions

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. Res