A Generalized Insertion Heuristic for the Traveling Salesman Problem with Time Windows

Gendreau, Michel; Hertz, Alain; Laporte, Gilbert; Stan, Mihnea

doi:10.1287/opre.46.3.330

Cited by 178 publications

(124 citation statements)

References 14 publications

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“…To group together similar requests, the level of attraction between two requests is measured by the proximity between their pickup and delivery locations. As observed by Gendreau et al (1998b), it does not suffice to define neighborhoods using only distances or travel times, since two locations close to each other may have time windows that are far apart or even incompatible. Hence, both the spatial and time dimensions have to be considered in the characterization of a neighborhood.…”

Section: Neighborhoodsmentioning

confidence: 99%

Dynamic transportation of patients in hospitals

Beaudry¹,

et al. 2008

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This paper analyzes and solves a patient transportation problem arising in several large hospitals. The aim is to provide an efficient and timely transport service to patients between several locations on a hospital campus. Transportation requests arrive in a dynamic fashion and the solution methodology must therefore be capable of quickly inserting new requests in the current vehicle routes. Contrary to standard dial-a-ride problems, the problem under study contains several complicating constraints which are specific to a hospital context. The paper provides a detailed description of the problem and proposes a two-phase heuristic procedure capable of handling its many features. In the first phase a simple insertion scheme is used to generate a feasible solution, which is improved in the second phase with a tabu search algorithm. The heuristic procedure was extensively tested on real data provided by a German hospital. Results show that the algorithm is capable of handling the dynamic aspect of the problem and of providing high quality solutions. In particular, it succeeded in reducing waiting times for patients while using fewer vehicles.

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Section: Neighborhoodsmentioning

confidence: 99%

Dynamic transportation of patients in hospitals

Beaudry¹,

et al. 2008

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“…Since finding feasible solutions to the TSPTW and m-TSPTW are NP-hard problems, most research has focused on heuristic algorithms [6,13,18,19,32]. These approaches are reviewed later in this paper.…”

Section: Introductionmentioning

confidence: 99%

Container movement by trucks in metropolitan networks: modeling and optimization

Jula

Dessouky

Ioannou

et al. 2005

Transportation Research Part E: Logistics and Transportation Re

117

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“…For example, the first vertex is visited at time 2, and the second vertex is visited no earlier than the preceding vertex. In 1998, Gendreau et al [27] mentioned a heuristic method, a generalized insertion heuristic for the TSPTW. This formulation is closer to what the USVOPP requires, but since our goal is to maximize the value collected at each point, and not necessarily visit each point and find the minimum distance, we need to explore a method that maximizes value.…”

Section: The Traveling Salesman Problem With Time Windows (Tsptw)mentioning

confidence: 99%

Large-Scale Dynamic Observation Planning for Unmanned Surface Vessels

Miller

2009

AIAA Infotech@Aerospace Conference

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With recent advances in research and technology, autonomous surface vessel capabilities have steadily increased. These autonomous surface vessel technologies enable missions and tasks to be performed without the direction of human operators, and have changed the way scientists and engineers approach problems. Because these robotic devices can work without manned guidance, they can execute missions that are too difficult, dangerous, expensive, or tedious for human operators to attempt. The United States government is currently expanding the use of autonomous surface vessel technologies through the United States Navy's Spartan Scout unmanned surface vessel (USV) and NASA's Ocean-Atmosphere Sensor Integration System (OASIS) USV. These USVs are well-suited to complete monotonous, dangerous, and time-consuming missions. The USVs provide better performance, lower cost, and reduced risk to human life than manned systems.In this thesis, we explore how to plan multiple USV observation schedules for two significant notional observation scenarios, collecting water temperatures ahead of the path of a hurricane, and collecting fluorometer readings to observe and track a harmful algal bloom. A control system must be in place that coordinates a fleet of USVs to targets in an efficient manner.We develop three algorithms to solve the unmanned surface vehicle observation-planning problem. A greedy construction heuristic runs fastest, but produces suboptimal plans; a 3-phase algorithm which combines a greedy construction heuristic with an improvement phase and an insertion phase, requires more execution time, but generates significantly better plans; an optimal mixed integer programming algorithm produces optimal plans, but can only solve small problem instances.

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A Generalized Insertion Heuristic for the Traveling Salesman Problem with Time Windows

Cited by 178 publications

References 14 publications

Dynamic transportation of patients in hospitals

Dynamic transportation of patients in hospitals

Container movement by trucks in metropolitan networks: modeling and optimization

Large-Scale Dynamic Observation Planning for Unmanned Surface Vessels

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