Globalization and digitalization have lead to new challenges and perspectives in intermodal transport logistics of large city sea ports and megahubs. In particular, due to an enormous increase of the container throughput over the last decades and the automatization of megahubs, new planning problems in this field must consistently be addressed by smart software solutions. In this research article, we sketch some challenges that arise at megahubs and outline how mechanism design, as a popular tool that combines ideas from game theory and computer science, can be an approach to tackle logistics problems that iolve multiple selfish players.
Container dispatching and conflict-free yard crane routing in an automated container terminal
(2018)
In this research, we focus on a container dispatching and conflict-free yard crane routing problem that arises at a storage yard in an automated, maritime container terminal. A storage yard serves as an intermediate buffer for import/export containers and exchanges containers between the waterside and landside of a maritime terminal. The considered storage yard is perpendicular to the waterside and employs two rail-mounted gantry cranes that have different sizes and thus have the possibility to cross each other. The problem at hand evaluates in which order and by which crane the import/export containers should be transported to minimize the makespan and prevent crane interferences. We solve this problem to optimality by a branch-and-cut approach that decomposes the problem into two problem classes and connects them via logic-based Benders constraints. We assess the quality of our solution method in a computational study.
The focus of this paper is on the windy rural postman problem with the additional option to zigzag street segments during certain times of the day. If a street is narrow or traffic is light, it is possible (and often desirable) to service both sides of the street in a single pass by zigzagging. However, if a street is wide or traffic is heavy, we must service the street by two single traversals. For some streets, we further assume that they may only be zigzagged early in the morning when the traffic is low. Real-life applications arise, among others, in trash collection and newspaper delivery. This problem is solved by transforming it into a node routing problem and present a mathematical formulation.
In this research, we focus on the windy rural postman problem with the additional option to zigzag street segments during certain times of the day. If a street is narrow or traffic is light, it is possible (and often desirable) to service both sides of the street in a single pass by zigzagging. However, if a street is wide or traffic is heavy, we must service the street by two single traversals. For some streets, we further impose the restriction that they may only be zigzagged at specific times of the day, e.g., in the early morning when there is virtually no traffic. Real-life applications arise, among others, in trash collection and newspaper delivery. This specific arc routing problem combines two classes of problems known from the literature, arc routing problems with zigzag options and arc routing problems with time dependencies. We present and discuss two (mixed) integer programming formulations for the problem at hand and suggest exact solution approaches. Furthermore, we analyze the effects of zigzag and time window options on the objective function value and test our solution approaches on real-world instances.
In combinatorial auctions, items are sold simultaneously. A substantial component of an auction mechanism is the pricing scheme. Prices determine the auctioneer’s revenue and, ideally, justify the outcome of the auction to the bidders. Each bidder should be able to see why he won or lost a certain bundle by comparing the determined price of a bundle and his bid’s value. In this paper, we pick up a non-linear anonymous pricing scheme from the literature that consists of a set of linear price vectors. We iestigate whether this scheme can guarantee to find prices that support the winner allocation. Furthermore, we refine the pricing scheme by suggesting various objectives in order to evaluate different prices. We consider the computational complexity of the corresponding optimization problems and compare different objectives by means of a computational study using a well-established combinatorial auction test suite.