Decision support for flexible liner shipping

We present a transportation problem representing a combination of liner and tramp shipping, where using other modes of transportation is also an option. As an example, we consider transportation of palletized frozen fish from Russia and Norway to terminals in Norway, the Netherlands, and the UK. We present a mathematical model for the planning problem associated with each tour and show that problem instances of realistic size can be solved to optimality using standard software.publishedVersio

The matching relaxation for a class of generalized set partitioning problems

This paper introduces a discrete relaxation for the class of combinatorial optimization problems which can be described by a set partitioning formulation under packing constraints. We present two combinatorial relaxations based on computing maximum weighted matchings in suitable graphs. Besides providing dual bounds, the relaxations are also used on a variable reduction technique and a matheuristic. We show how that general method can be tailored to sample applications, and also perform a successful computational evaluation with benchmark instances of a problem in maritime logistics.Comment: 33 pages. A preliminary (4-page) version of this paper was presented at CTW 2016 (Cologne-Twente Workshop on Graphs and Combinatorial Optimization), with proceedings on Electronic Notes in Discrete Mathematic

Including containers with dangerous goods in the Slot Planning Problem

Container stowage problems are rich optimization problems with both high economic and environmental impact. These problems are typically decomposed into a master bay planning phase, which distributes containers to bay sections of the vessel, and a slot planning phase, which assigns a specific slot within the bay section to each container. In this paper, we extend existing models for slot planning by considering containers with dangerous goods. An important contribution of this paper is that we provide a model closer to the real-world problems faced by planners, and thus solutions based on this model should be easier to implement in practice. We show that our model can be solved to optimality in reasonable time using standard software like Gurobi or CPLEX. Keywords: operations research, container stowage, optimization, logisticspublishedVersio

The Value of Inaccurate Advance Time Window Information in a Pick-up and Delivery Problem

We examine different routing strategies to cope with inaccurate time window in- formation in the context of a dynamic pick-up and delivery problem with time windows. Our experiments show that advance information, even if inaccurate, can provide benefits from a planning perspective. We propose a novel stochastic strategy that consistently performs well compared to several benchmark strategies

Strategies for Handling Temporal Uncertainty in Pickup and Delivery Problems with Time Windows

In many real-life routing problems there is more uncertainty with respect to the required timing of the service than with respect to the service locations. We focus on a pickup and delivery problem with time windows in which the pickup and drop-off locations of the service requests are fully known in advance, but the time at which these jobs will require service is only fully revealed during operations. We develop a sample-scenario routing strategy to accommodate a variety of potential time real- izations while designing and updating the routes. Our experiments on a breadth of instances show that advance time related information, if used intelligently, can yield benefits. Furthermore, we show that it is beneficial to tailor the consensus function that is used in the sample-scenario approach to the specifics of the problem setting. By doing so, our strategy performs well on instances with both short time windows and limited advance confirmation

Including Containers with Dangerous Goods in the Multi-Port Master Bay Planning Problem

In this paper we extend existing models for Master Bay Planning by handling containers holding dangerous goods, so-called IMO containers. Incompatible IMO containers must be separated from each other on board a vessel according to specic rules. These rules affect both Master Bay Planning and Slot Planning, which are the two planning problems normally handled in container stowage planning. Some research is done to include IMO containers in Slot Planning, but, to the best of our knowledge, this is the rst time handling of IMO containers is included in Master Bay Planning. We present results from computational tests showing that our model can be solved to optimality, or near optimality, in reasonable time for realistically sized instances

A sustainable model for optimal dynamic allocation of patrol tugs to oil tankers

publishedVersio

An Attribute Based Similarity Function for VRP Decision Support

When solving problems in the real world using optimization tools, the model solved by the tools is often only an approximation of the underlying, real, problem. In these circumstances, a decision maker (DM) should consider a diverse set of good solutions, not just an optimal solution as produced using the model. On the other hand, the same DM will only be interested in seeing a few of the alternative solutions, and not the plethora of solutions often produced by modern search techniques. There is thus a need to distinguish between good solutions using the attributes of solutions. We develop a distance function of the type proposed in the Psychology literature by Tversky (1977) for the class of VRP problems. We base our difference on the underlying structure of solutions.A DM is often interested in focusing on a set of solutions fulfilling certain conditions that are of specific importance that day, or in general, like avoiding a certain road due to construction that day. This distance measure can also be used to generate solutions containing these specific classes of attributes, as the normal search process might not supply enough of these interesting solutions. We illustrate the use of the functions in a Multiobjective Decision Support System (DSS) setting, where the DM might want to see the presence (or absence) of certain attributes, and show the importance of identifying solutions not on the Pareto front. Our distance measure can use any attributes of the solutions, not just those defined in the optimization model

Isabelle/PIDE as Platform for Educational Tools

The Isabelle/PIDE platform addresses the question whether proof assistants of the LCF family are suitable as technological basis for educational tools. The traditionally strong logical foundations of systems like HOL, Coq, or Isabelle have so far been counter-balanced by somewhat inaccessible interaction via the TTY (or minor variations like the well-known Proof General / Emacs interface). Thus the fundamental question of math education tools with fully-formal background theories has often been answered negatively due to accidental weaknesses of existing proof engines. The idea of "PIDE" (which means "Prover IDE") is to integrate existing provers like Isabelle into a larger environment, that facilitates access by end-users and other tools. We use Scala to expose the proof engine in ML to the JVM world, where many user-interfaces, editor frameworks, and educational tools already exist. This shall ultimately lead to combined mathematical assistants, where the logical engine is in the background, without obstructing the view on applications of formal methods, formalized mathematics, and math education in particular.Comment: In Proceedings THedu'11, arXiv:1202.453