Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem

Masmoudi, Mohamed Amine; Hosny, Manar; Braekers, Kris; Dammak, Abdelaziz

doi:10.1016/j.tre.2016.10.002

Cited by 79 publications

(63 citation statements)

References 59 publications

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“…This process continues until an acceptable solution is found or a maximum number of iterations is reached. In order to minimize the number of required iterations, and thus the computation time, the classical ALNS can be improved by adding a score to each operator (Masmoudi et al (2016)). If using one operator, whether it is an insertion or removal operator, brings an improvement to the current solution, then the score of the operator used will be increased.…”

Section: Computational Complexity and Solution Approachesmentioning

confidence: 99%

A survey of models and algorithms for optimizing shared mobility

Mourad

Puchinger

Chu

2019

Transportation Research Part B: Methodological

238

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The rise of research into shared mobility systems reflects emerging challenges, such as rising traffic congestion, rising oil prices and rising environmental concern. The operations research community has turned towards more sharable and sustainable systems of transportation. Shared mobility systems can be collapsed into two main streams: those where people share rides and those where parcel transportation and people transportation are combined. This survey sets out to review recent research in this area, including different optimization approaches, and to provide guidelines and promising directions for future research. It makes a distinction between prearranged and real-time problem settings and their methods of solution, and also gives an overview of real-case applications relevant to the research area.

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Section: Computational Complexity and Solution Approachesmentioning

confidence: 99%

A survey of models and algorithms for optimizing shared mobility

Mourad

Puchinger

Chu

2019

Transportation Research Part B: Methodological

238

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“…To best of our knowledge, the hybrid GA provides the best-known results on these instances so far and outperforms current state-of-the-art algorithms for the standard DARP and HDARP. In another study, Masmoudi et al [15] augment the multi depots and coffee break concepts on the standard HDARP. They propose hybrid methods based on nature-inspired algorithms and tested them on both newly generated instances and on the benchmark Multi-Depot HDARP instances of Braekers et al [13].…”

Section: The Heterogenous Dial-a Ride-problemmentioning

confidence: 99%

“…Constraints (14) impose time windows compliance. Constraints (15) ensure that the time duration of the route for each vehicle is limited by . Constraints (16) impose that the fuel level is reduced based on the distance travelled between nodes and and the fuel consumption rate, where is a constant applied to each arc ( , ) ∀ , ∈ ′.…”

Section: Problem Definition and Model Formulationmentioning

confidence: 99%

Container truck transportation routing as a Mixed Fleet Heterogeneous Dial-a-Ride Problem

et al. 2020

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In this paper, a new variant of the Heterogeneous Dial-a-Ride Problem (HDARP) is innovatively applied to a routing problem of trucks picking up and delivering full and empty containers in the logistic chain, including container depots, importers demanding full containers and exporters requesting empty containers. On the route different types of trucks pick-up and deliver full and empty 20-and 40-foot containers. We consider trucks that are operated by alternative fuel, as well as the need for refuelling of trucks in any alternative fuel station to eliminate the risk of running out of fuel during its route. The objective of the paper is to contribute to the optimization of container truck transport routing with multiple pickups and deliveries by providing a mathematical programming model aiming at minimizing the transportation cost as well as the negative environmental impacts.

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“…Masson et al [15] described an adaptive large neighborhood search (ALNS) algorithm for the DARP with transfer points, where users can transfer to different vehicles during their trip at predefined points. On real-life instances, the algorithm generated around 8% of cost savings Masmoudi et al [16] studied a variant called the multi-depot multi-trip heterogeneous DARP (MD-MT-HDARP). They proposed three different metaheuristics: an improved ALNS, a hybrid Bees Algorithm with Simulated Annealing (BA-SA), and a hybrid Bees Algorithm with Deterministic Annealing (BA-DA).…”

Section: Alns Darp Applicationsmentioning

confidence: 99%

A Hybrid Adaptive Large Neighborhood Heuristic for a Real-Life Dial-a-Ride Problem

Belhaiza

2019

Algorithms

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The transportation of elderly and impaired people is commonly solved as a Dial-A-Ride Problem (DARP). The DARP aims to design pick-up and delivery vehicle routing schedules. Its main objective is to accommodate as many users as possible with a minimum operation cost. It adds realistic precedence and transit time constraints on the pairing of vehicles and customers. This paper tackles the DARP with time windows (DARPTW) from a new and innovative angle as it combines hybridization techniques with an adaptive large neighborhood search heuristic algorithm. The main objective is to improve the overall real-life performance of vehicle routing operations. Real-life data are refined and fed to a hybrid adaptive large neighborhood search (Hybrid-ALNS) algorithm which provides a near-optimal routing solution. The computational results on real-life instances, in the Canadian city of Vancouver and its region, and DARPTW benchmark instances show the potential improvements achieved by the proposed heuristic and its adaptability.

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Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem

Cited by 79 publications

References 59 publications

A survey of models and algorithms for optimizing shared mobility

A survey of models and algorithms for optimizing shared mobility

Container truck transportation routing as a Mixed Fleet Heterogeneous Dial-a-Ride Problem

A Hybrid Adaptive Large Neighborhood Heuristic for a Real-Life Dial-a-Ride Problem

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