Article
Chemistry, Multidisciplinary
Mehmet Anil Akbay, Can Berk Kalayci, Christian Blum, Olcay Polat
Summary: This paper proposes a method to solve the two-echelon electric vehicle routing problem, aiming to reduce the negative impact in urban areas through multi-echelon distribution networks and environmentally friendly vehicles. A mixed-integer linear programming model is developed, and a variable neighborhood search metaheuristic is proposed to improve the solution quality.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Interdisciplinary Applications
Timo Hintsch
Summary: The paper introduces a large multiple neighborhood search algorithm for the SoftCluVRP, utilizing various cluster destroy and repair operators and two post optimization components. Computational experiments demonstrate that the algorithm outperforms existing heuristic approaches and provides 130 new best solutions for medium-sized instances.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Economics
Mir Ehsan Hesam Sadati, Bulent Catay
Summary: The Multi-Depot Green Vehicle Routing Problem extends the well-known GVRP and proposes new neighborhood structures to effectively solve the problem. Evaluation using literature dataset shows high performance of the method in providing high quality solutions in short computation times.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Computer Science, Interdisciplinary Applications
Mir Ehsan Hesam Sadati, Bulent Catay, Deniz Aksen
Summary: The VTNS algorithm is a flexible algorithm for solving Multi-Depot Vehicle Routing Problems, capable of adapting to different types of problems and providing competitive results in terms of solution quality and run time.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Mathematics
Yusuf Yilmaz, Can B. Kalayci
Summary: This paper addresses the Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery, proposing an efficient solution using an integer linear model and variable neighborhood search algorithm to minimize total distance traveled. Experimental results show that the proposed method achieves efficient solutions in terms of solution quality and time.
Article
Computer Science, Interdisciplinary Applications
Sinaide Nunes Bezerra, Marcone Jamilson Freitas, Sergio Ricardo de Souza
Summary: This article addresses the MDVRPTW* problem and proposes an algorithm called SGVNSALS to solve it. The algorithm outperforms other algorithms in terms of the number of used vehicles and covered distance.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Software Engineering
Erdener Ozcetin, Gurkan Ozturk
Summary: This study discusses the Open Vehicle Routing Problem commonly used by companies with third-party logistics services, which belongs to the class of high-dimensional and complex optimization problems. A three-phase Variable Neighborhood Search Algorithm is proposed to efficiently solve large-scale problems. The algorithm utilizes eight different neighborhoods and employs wise shaking strategies to overcome local optimal solutions. The method's competitiveness is tested on literature test instances and comparatively evaluated.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Panagiotis Kalatzantonakis, Angelo Sifaleras, Nikolaos Samaras
Summary: This paper proposes a new hyperheuristic scheme, called Bandit VNS, that utilizes reinforcement learning methods to improve the performance of Variable Neighborhood Search. By modifying the Upper Confidence Bound algorithm and utilizing Adaptive Windowing, Bandit VNS achieves better solution quality and speed in solving complex problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics
Lamiaa Dahite, Abdeslam Kadrani, Rachid Benmansour, Rym Nesrine Guibadj, Cyril Fonlupt
Summary: This paper addresses the problem faced by maintenance service providers in performing maintenance activities on geographically distributed machines. It proposes a new bi-objective mathematical model and algorithms to determine the optimal maintenance and routing plan simultaneously. The efficiency of the approach is demonstrated through experiments.
Article
Economics
Dorian Dumez, Fabien Lehuede, Olivier Peton
Summary: This article proposes a solution for last mile delivery with multiple delivery options, successfully addressing specific cases of vehicle routing problems through large neighborhood search and specific operators.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Computer Science, Interdisciplinary Applications
Xin Wang, Yijing Liang, Xiaoyang Wei, Ek Peng Chew
Summary: Seaports are crucial for connecting inland and maritime transportation, and tugboats play a vital role in providing enough power and ensuring safety for container ships when entering and leaving seaports. Thus, scheduling tugboats in seaport management is essential to facilitate the cost-effective movement of container ships. This paper investigates the tugboat scheduling problem considering multiple services at multiple waypoints to optimize the utilization of limited tugboats. An efficient adaptive large neighborhood search algorithm with a feasibility check procedure is proposed and validated through computational experiments, providing valuable managerial insights based on sensitivity analysis.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Information Systems
Meiling He, Zhixiu Wei, Xiaohui Wu, Yongtao Peng
Summary: An adaptive variable neighborhood search ant colony algorithm (AVNSACA) is proposed to solve the VRPSTW problem, which improves the pheromone update strategy and designs variable neighborhood search operators to avoid the algorithm falling into local optima. Experimental results demonstrate the effectiveness of the AVNSACA in obtaining better solutions for vehicle routing with soft time windows.
Article
Computer Science, Artificial Intelligence
Ran Liu, Shan Jiang
Summary: This paper discusses the two-echelon vehicle routing problem with simultaneous delivery and pickup demands (2E-VRPSDP), which differs from classic transportation and vehicle routing problems. A variable neighborhood search algorithm is proposed to solve the problem, and numerical results show that the algorithm can provide reasonable solutions within an acceptable computational time.
Article
Operations Research & Management Science
Luigi Di Puglia Pugliese, Daniele Ferone, Paola Festa, Francesca Guerriero, Giusy Macrina
Summary: Crowd-shipping is an innovative delivery model based on the sharing economy concept, utilizing underused resources through a crowd-shipping platform connecting the company, occasional drivers, and customers. This paper develops an approach inspired by variable neighborhood search (VNS) method, employing machine learning techniques to enhance the effectiveness of the basic framework.
OPTIMIZATION LETTERS
(2023)
Article
Management
Adolfo Urrutia-Zambrana, Gregorio Tirado, Alfonso Mateos
Summary: This paper introduces a variable neighborhood search algorithm to solve the generalized orienteering problem, outperforming all previous metaheuristics by reducing the number of neighborhoods and precalculating scores. It discovered 35 new best solutions in the case studies and improved information on other best-known solutions by correcting errors and adding new real data case studies from popular tourist cities in Spain.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2021)
