Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search

Turkeš, Renata; Sörensen, Kenneth; Hvattum, Lars Magnus

doi:10.1016/j.ejor.2020.10.045

Cited by 42 publications

(6 citation statements)

References 104 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the tabu search [80], simulated annealing [296], memetic algorithm [301] and an auxiliary algorithm [89], for instance, it serves as the initialization technique. In large neighborhood search [285], it is employed as a recreate operation.…”

Section: Nearest Neighbor Methodsmentioning

confidence: 99%

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances

Liu¹,

Lu²,

Gui³

et al. 2023

Preprint

View full text Add to dashboard Cite

Vehicle routing is a well-known optimization research topic with significant practical importance. Among different approaches to solving vehicle routing, heuristics can produce a satisfactory solution at a reasonable computational cost. Consequently, much effort has been made in the past decades to develop vehicle routing heuristics. In this article, we systematically survey the existing vehicle routing heuristics, particularly on works carried out in recent years. A classification of vehicle routing heuristics is presented, followed by a review of their methodologies, recent developments, and applications. Moreover, we present a general framework of state-of-the-art methods and provide insights into their success. Finally, three emerging research topics with notable works and future directions are discussed.

show abstract

Section: Nearest Neighbor Methodsmentioning

confidence: 99%

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances

Liu¹,

Lu²,

Gui³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…LNS has been successfully applied to many variants of vehicle routing problems [Pisinger and Ropke, 2019] and the literature is abundant. Recently, Turkeš et al [2019] compiled many papers using an LNS heuristic in a meta-analysis that concludes that the adaptive component proposed by Ropke and Pisinger [2006a] has, at best, a small impact.…”

Section: Solution Methodsmentioning

confidence: 99%

A large neighborhood search approach to the vehicle routing problem with delivery options

Dumez

Lehuédé

Péton

2021

Transportation Research Part B: Methodological

View full text Add to dashboard Cite

To reduce delivery failures in last mile delivery, several types of delivery options have been proposed in the past twenty years. Still, customer satisfaction is a challenge because a single location is chosen independently of the time at which customers will be delivered. In addition, delivery in shared locations such as lockers and shops also experience failure due to capacity or opening-time issues at the moment of delivery. To address this issue and foster consolidation in shared delivery points, we investigate the case where a customer can specify several delivery options together with preference levels and time windows. We define, in this article, the Vehicle Routing Problem with Delivery Options, which integrates several types of delivery locations. It consists of designing a set of routes for a fleet of vehicles that deliver to each customer at one of his/her options during the corresponding time window. These routes should respect capacities at shared locations such as lockers and minimum service level requirements, while minimizing the total routing costs. To solve this problem, we have designed a large neighborhood search in which a set partitioning problem is solved to regularly reassemble routes. Specific ruin and recreate operators are proposed and combined with numerous operators from the literature. A thorough experimental study was carried out to determine a subset of efficient and complementary operators. The proposed method outperforms existing algorithms from the literature on particular cases of the problem under consideration, such as the vehicle routing problem with roaming delivery locations and the vehicle routing problem with home and roaming delivery locations. New instances are generated and used both to serve as a benchmark and to propose some managerial insight into the vehicle routing problem with alternative delivery options.

show abstract

“…However, when it is close to the optimal solution, it is not easy to find the optimal solution because of the large search step of the enhance disturbance strategy. In the solution process, if the search step can be changed adaptively, it can not only improve the convergence speed of the algorithm, but also find the most suitable solution more accurately when it is close to the global optimal solution [28,31]. In view of this situation, we design an adaptive strength disturbance strategy, which can adaptively switch between asynchronous and long disturbance operators according to the historical iterative evolution information.…”

Section: Adaptive Strength Perturbation and Random Strength Perturbat...mentioning

confidence: 99%

Variable neighborhood optimization for automatic warehouse in and out based on collaborative cooperation

Guo

Wei

Liu

et al. 2023

Preprint

View full text Add to dashboard Cite

In the process of warehouse automation, an efficient order picking strategy is one of the key factors affecting the efficiency of warehousing. Based on the characteristics of orders and stackers, the picking order model of stackers entering and exiting the warehouse is considered as a prize collection vehicle routing problem (PCVRP) for picking and delivering goods simultaneously. When solving this problem, The adaptive strength perturbation strategy is proposed to improve the convergence speed of the algorithm. In the process of population evolution, the random intensity perturbation strategy is introduced to ensure the diversity of the solution space. To balance the local search and global convergence capabilities of the algorithm, a hybrid iterative local search and variable neighborhood search (HILS-VND) collaborative optimization algorithm is designed. The experimental results indicate that, compared with several other existing algorithm, the proposed algorithm outperforms the comparison algorithms on standard evaluation indicators such as hypervolume, the number of non-dominated solutions and spacing metric.

show abstract

Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search

Cited by 42 publications

References 104 publications

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances

A large neighborhood search approach to the vehicle routing problem with delivery options

Variable neighborhood optimization for automatic warehouse in and out based on collaborative cooperation

Contact Info

Product

Resources

About