The Vehicle Routing Problem with Service Level Constraints

We consider a vehicle routing problem which seeks to minimize cost subject to service level constraints on several groups of deliveries. This problem captures some essential challenges faced by a logistics provider which operates transportation services for a limited number of partners and should respect contractual obligations on service levels. The problem also generalizes several important classes of vehicle routing problems with profits. To solve it, we propose a compact mathematical formulation, a branch-and-price algorithm, and a hybrid genetic algorithm with population management, which relies on problem-tailored solution representation, crossover and local search operators, as well as an adaptive penalization mechanism establishing a good balance between service levels and costs. Our computational experiments show that the proposed heuristic returns very high-quality solutions for this difficult problem, matches all optimal solutions found for small and medium-scale benchmark instances, and improves upon existing algorithms for two important special cases: the vehicle routing problem with private fleet and common carrier, and the capacitated profitable tour problem. The branch-and-price algorithm also produces new optimal solutions for all three problems

New technologies in making orienteering maps

Orienteering maps are special type of maps, which are mostly made by non-professionals. The technology of making these maps (fieldwork, drawing) has considerably changed in the last 20 years. Base maps can be made by digital photogrammetry or airborne laser scanning technology, but the methods of creating state topographic maps (which are used as base maps of orienteering maps) have also changed in the past few years. The accuracy of these maps has also increased to help the users. In the fieldworking, we can use GPS devices (sometimes with real-time differential corrections) for measuring points and lines. GPS devices are available for more than 20 years, but only in the last few years they became used in fieldworking as regular techniques. For faster, but not very accurate distance measurements, we can use ordinary laser distance finders. The orienteering maps are drawn by computer software. In some countries, these were the first types of maps which were created only by computer methods. Orienteering maps are good indicators of how the new cartographic techniques are easily applicable for non-professionals or how widely they are used as everyday techniques. This paper summarizes the milestones of the development of these techniques to understand how we can make these methods and devices more user-friendly and simpler

Tour recommendation for groups

Consider a group of people who are visiting a major touristic city, such as NY, Paris, or Rome. It is reasonable to assume that each member of the group has his or her own interests or preferences about places to visit, which in general may differ from those of other members. Still, people almost always want to hang out together and so the following question naturally arises: What is the best tour that the group could perform together in the city? This problem underpins several challenges, ranging from understanding people’s expected attitudes towards potential points of interest, to modeling and providing good and viable solutions. Formulating this problem is challenging because of multiple competing objectives. For example, making the entire group as happy as possible in general conflicts with the objective that no member becomes disappointed. In this paper, we address the algorithmic implications of the above problem, by providing various formulations that take into account the overall group as well as the individual satisfaction and the length of the tour. We then study the computational complexity of these formulations, we provide effective and efficient practical algorithms, and, finally, we evaluate them on datasets constructed from real city data

DISCRETE PARTICLE SWARM OPTIMIZATION FOR THE ORIENTEERING PROBLEM

Discrete particle swarm optimization (DPSO) is gaining popularity in the area of combinatorial optimization in the recent past due to its simplicity in coding and consistency in performance.  A DPSO algorithm has been developed for orienteering problem (OP) which has been shown to have many practical applications.  It uses reduced variable neighborhood search as a local search tool.  The DPSO algorithm was compared with ten heuristic models from the literature using benchmark problems.  The results show that the DPSO algorithm is a robust algorithm that can optimally solve the well known OP test problems

The orienteering problem: A hybrid control Formulation

In the last years, a growing number of challenging applications in navigation, logistics, and tourism were modeled as orienteering problems. This problem has been proposed in relation to a sport race where certain control points must be visited in a minimal time. In a certain kind of these competitions, the choice of the number and the order for the control points are left to the competitor. We propose an original approach to solve the orienteering problem based on hybrid control. The continuous state of the system contains information about the navigation toward the next control point. In contrast, the discrete state keeps track of the already visited ones. The control problem is solved using non-standard dynamical programming techniques

Practical Route Planning Algorithm

Routing algorithms are traditionally considered to apply thesum of profits gathered at visited locations as an objectivefunction since the Traveling Salesman Problem. This heritagedisregards many practical considerations, hence the result ofthese models meet with user’s needs rarely.Thus considering the importance of this theoretical and modelingproblem, a novel objective function will be presented inthis paper as an extension of the one inherited from the TSPthat is more aligned with user preferences and aims to maximizethe tourist’s satisfaction. We also propose a heuristicalgorithm to solve the Team Orienteering Problem with relativelylow computation time in case of high number of verticeson the graph and multiple tour days. Based on the key performanceindicators and user feedback the algorithm is suitableto be implemented in a GIS application considering that even a3-day tour is designed less than 4 seconds