Congestion avoidance: optimization of vehicle routing planning for the logistics industry

This research focuses on the development of ecient solution methods to solve time dependent orienteering problems (TD-OP) in real time. Orienteering problems are used in logistic and touristic cases were an optimal combination of locations needs to be selected and the routing between the locations needs to be optimized. In the time dependent variant the travel time between two locations depends on the departure time at the rst location

Orienteering problem with hotel selection: a variable neighborhood search method

In this research, we developed a skewed variable neighbourhood search algorithm to solve the orienteering problem (OP) with hotel selection, a non-investigated variant of the OP. We also designed two appropriate sets of benchmark instances with known optimal solutions. Applying the proposed algorithm on these instances shows the quality of the algorithm. The algorithm is also fast enough to be implemented in a tourist application

Improving the robustness of the railway system in Brussels

In order to improve the robustness of a railway system in station areas, this paper introduces an iterative approach to successively solve the route choice problem in station areas to optimality and to improve this solution by applying some changes to the timetable in a tabu search environment. Using a discrete event simulation model, the performance of our algorithms is evaluated based on a case study for the Brussels' area. The railway network of the Brussels' area is introduced and its relevance is emphasized. Computational results indicate an improvement in robustness of about 10%, a decrease in knock-on delay of more than 15%, and a 25% reduction in the number of trains that are confronted with conflicts

Improved methods for the travelling salesperson problem with hotel selection

In this talk, a new formulation and a new metaheuristic solution procedure for the travelling salesperson problem with hotel selection (TSPHS) is presented. The metaheuristic is a multi-start procedure that outperforms existing heuristics on all benchmark instances. We also provide a number of new optimal solutions found by a commercial solver extended with a dedicated cutting plane procedure, as well as new best known solutions for most benchmark instances

Tourist trip planning functionalities : state-of-the-art and future

When tourists visit a city or region, they cannot visit every point of interest available, as they are constrained in time and budget. Tourist recommender applications help tourists by presenting a personal selection. Providing adequate tour scheduling support for these kinds of applications is a daunting task for the application developer. The objective of this paper is to demonstrate how existing models from the field of Operations Research (OR) fit this scheduling problem, and enable a wide range of tourist trip planning functionalities. Using the Orienteering Problem (OP) and its extensions to model the tourist trip planning problem, allows to deal with a vast number of practical planning problems

Heuristics for the traveling repairman problem with profits

In the traveling repairman problem with profits, a repairman (also known as the server) visits a subset of nodes in order to collect time-dependent profits. The objective consists of maximizing the total collected revenue. We restrict our study to the case of a single server with nodes located in the Euclidean plane. We investigate properties of this problem, and we derive a mathematical model assuming that the number of visited nodes is known in advance. We describe a tabu search algorithm with multiple neighborhoods, and we test its performance by running it on instances based on TSPLIB. We conclude that the tabu search algorithm finds good-quality solutions fast, even for large instances