Time dependent orienteering problem with time windows and service time dependent profits

Khodadadian, M.; Divsalar, Ali; Verbeeck, Cédric; Gunawan, Aldy; Vansteenwegen, Pieter

doi:10.1016/j.cor.2022.105794

Cited by 20 publications

(5 citation statements)

References 48 publications

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“…We plan to extend our approach to other TD routing problems such as, for example, TD vehicle routing problems (Chen et al, 2006), TD orienteering problems (Khodadadian et al, 2022), TD inventory routing problems (Touzout et al, 2022) or TD profitable pickup and delivery problems (Sun et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Exact and anytime approach for solving the time dependent traveling salesman problem with time windows

Fontaine

Dibangoye

Solnon

2023

European Journal of Operational Research

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Section: Discussionmentioning

confidence: 99%

Exact and anytime approach for solving the time dependent traveling salesman problem with time windows

Fontaine

Dibangoye

Solnon

2023

European Journal of Operational Research

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“…A new OP variant with service time dependent profits and time dependent travel times was investigated by [12]. The authors proposed an MILP mathematical formulation and a VNS metaheuristic based on three specialized neighborhood structures.…”

Section: Brief Literature Reviewmentioning

confidence: 99%

“…Constraint (9) imposes the minimum QoS. Constraints (10), (11), and (12) give the domain of the decision variables.…”

Section: Mathematical Modelmentioning

confidence: 99%

An iterated local search for a multi‐period orienteering problem arising in a car patrolling application

Vidigal Corrêa,

Dong,

Iori

et al. 2023

Networks

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This paper addresses a real‐world multi‐period orienteering problem arising in a large Italian company that needs to patrol an area in order to provide security services to a set of customers. Each customer requires different services on a weekly basis. Some services are mandatory, while others are optional. It might be impossible to perform all optional services, and each of them is assigned a score when performed. The challenge is to determine a set of routes, one per day, that maximizes a weighted sum of the total collected score and total working time, while meeting several operational constraints, including hard time windows, maximum riding time, minimum number of services performed, and minimum time between two consecutive visits for the same service at the same customer. To solve the problem, we propose an iterated local search that invokes at each iteration an inner variable neighborhood descent procedure. Computational tests performed on a large number of real‐world instances prove that the developed algorithm is very efficient, and finds in a short time solutions that are consistently better than those produced by a mathematical model, and those in use at the company.

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“…The only difference between the OPHS-TW and OPHS is that each POI in the OPHS-TW is assigned a time window [ Oi , Ci ]. Khodadadian et al ( 25 ) addressed the time-dependent OP with time windows, which considers a given time budget and time windows. Divsalar et al ( 26 ) proposed a hybrid heuristic algorithm to solve the OPHS-TW.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization for the Multiday Urban Personalized Trip Design Problem With Time Windows and Transportation Mode Recommendations

Jian

Wang

2023

Transportation Research Record: Journal of the Transportation R

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The urban tourism market has been increasingly dominated by the demand for personalized experiences. This paper focuses on the multiday urban personalized trip design problem considering the time windows and transportation mode recommendations (MUPTDP-TW-TMR). A two-stage methodology is proposed to solve this problem. In the first stage, a linear programming model for the multiday urban personalized trip design problem with time windows (MUPTDP-TW) is proposed. A modified memetic algorithm (MMA) is devised to solve it, containing efficient operators. In the second stage, a novel transportation mode recommendation model is developed, which considers the diversity of tourist preferences. A modified label-setting algorithm is applied to solve the model. The data from Chongqing, the most popular city in Southwest China, are collected to evaluate the performance of our approach. The case study based on tourist and popular preferences is conducted. Compared with the state-of-the-art algorithms, the experimental results show that our approach can design more reasonable and personalized itineraries for tourists.

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Time dependent orienteering problem with time windows and service time dependent profits

Cited by 20 publications

References 48 publications

Exact and anytime approach for solving the time dependent traveling salesman problem with time windows

Exact and anytime approach for solving the time dependent traveling salesman problem with time windows

An iterated local search for a multi‐period orienteering problem arising in a car patrolling application

Optimization for the Multiday Urban Personalized Trip Design Problem With Time Windows and Transportation Mode Recommendations

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