An iterative three-component heuristic for the team orienteering problem with time windows

Hu, Qian; Lim, Andrew

doi:10.1016/j.ejor.2013.06.011

Cited by 86 publications

(51 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cura [29] propose an artificial bee colony approach to solve the TOPTW which achieves comparable results. Hu and Lim [65] propose an iterative three-component heuristic for the TOPTW. The first two components are a local search procedure and a simulated annealing procedure by which the solution space is explored and a set of routes is discovered.…”

Section: The Team Orienteering Problem (With Time Windows)mentioning

confidence: 99%

Optimizing practical orienteering problems with stochastic time-dependent travel times: towards congestion free routes

Verbeeck¹

2016

4OR-Q J Oper Res

View full text Add to dashboard Cite

Section: The Team Orienteering Problem (With Time Windows)mentioning

confidence: 99%

Optimizing practical orienteering problems with stochastic time-dependent travel times: towards congestion free routes

Verbeeck¹

2016

4OR-Q J Oper Res

View full text Add to dashboard Cite

“…According to the number of time windows, the TOP can be further divided into single time window (TOP-TW) or multiple time windows (TOP-MTW) problems, which are NP-hard problems [37]. In the TOP-TW, each vertex has a fixed time window [11,38,39], and the time window constraints require that the visit to the vertex must start within the specified time [40]. In the TOP-MTW, each vertex can have multiple fixed time windows.…”

Section: Related Workmentioning

confidence: 99%

Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

Luo

Niu

Zhu

et al. 2017

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Task allocation is the key factor in the spraying pesticides process using unmanned aerial vehicles (UAVs), and maximizing the effects of pesticide spraying is the goal of optimizing UAV pesticide spraying. In this study, we first introduce each UAV's kinematic constraint and extend the Euclidean distance between fields to the Dubins path distance. We then analyze the two factors affecting the pesticide spraying effects, which are the type of pesticides and the temperature during the pesticide spraying. The time window of the pesticide spraying is dynamically generated according to the temperature and is introduced to the pesticide spraying efficacy function. Finally, according to the extensions, we propose a team orienteering problem with variable time windows and variable profits model. We propose the genetic algorithm to solve the above model and give the methods of encoding, crossover, and mutation in the algorithm. The experimental results show that this model and its solution method have clear advantages over the common manual allocation strategy and can provide the same results as those of the enumeration method in small-scale scenarios. In addition, the results also show that the algorithm parameter can affect the solution, and we provide the optimal parameters configuration for the algorithm.

show abstract

“…Kim et al [9] proposed an augmented large neighborhood search (LNS) for the same problem. Finally, Hu and Lim [8] proposed an iterative three-component heuristic for a TOP with time windows, i.e., a time window is associated with each vertex. The reader can refer to Vidal et al [13] that published a survey on the different heuristics used for solving the multi-attribute vehicle routing problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Remember that path P k ∈ P must start from the start point v 0 , visits a subset of vertices in V and ends at vertex v n+1 . η * ← η 0 ; (the best solution found for the k th path) 8:…”

Section: A Beam Search For Computing Pathsmentioning

confidence: 99%

A hybrid heuristic for the team orienteering problem

Bouchakhchoukha

Menouer

Sukhija

2017

2017 IEEE SmartWorld, Ubiquitous Intelligence &Amp; Computing, Advanced &Amp; Trusted Computed, Scalable Computing &Amp; Commun

View full text Add to dashboard Cite

Abstract-In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.

show abstract

An iterative three-component heuristic for the team orienteering problem with time windows

Cited by 86 publications

References 27 publications

Optimizing practical orienteering problems with stochastic time-dependent travel times: towards congestion free routes

Optimizing practical orienteering problems with stochastic time-dependent travel times: towards congestion free routes

Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm

A hybrid heuristic for the team orienteering problem

Contact Info

Product

Resources

About