Article
Engineering, Multidisciplinary
Alireza Eydi, Seyed Ali Ghasemi-Nezhad
Summary: This study proposed a new mathematical model through multi-objective optimization approach, making the logistic problems involving occasional goods in the real world more efficient. The research covers time windows, multiple demands, and two conflicting objectives, and proposes two metaheuristic algorithms.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Computer Science, Interdisciplinary Applications
Feng Wang, Fanshu Liao, Yixuan Li, Xuesong Yan, Xu Chen
Summary: This paper proposes a new algorithm EL-DMOEA for solving the Dynamic Vehicle Routing Problem with Time Window, using ensemble learning method to improve algorithm performance. Multiple strategies are employed during training process to enhance population diversity and accelerate convergence, with experimental results showing promising routing plans can be effectively developed by the proposed algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Seyed Zeinab Aliahmadi, Farnaz Barzinpour, Mir Saman Pishvaee
Summary: In this study, a bi-objective vehicle routing mathematical model was proposed and solved using Non-dominated Sorting Genetic Algorithm II, which achieved significant optimization results in terms of total economic cost and total time for waste collection.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Multidisciplinary
Chenghong Lv, Jianxin Xu
Summary: This article focuses on the distribution strategy problem for multi-compartment and single cabin vehicles under multi-objective conditions. It uses the NSGA-II algorithm and improved Large Scale Domain Search (ILNS) to experiment with Solomon dataset. The experiments show that multi-compartment vehicle fleets have significant advantages in transportation costs and a mixed fleet is more advantageous in terms of total costs.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Review
Green & Sustainable Science & Technology
Xiaobo Liu, Yen-Lin Chen, Lip Yee Por, Chin Soon Ku
Summary: Vehicle routing problems with time windows (VRPTW) have gained a lot of attention due to their important role in real-life logistics and transport. As a result of the complexity of real-life situations, most problems are multi-constrained and multi-objective, which increases their difficulty. This paper aims to contribute to the effective solution of VRPTW-related problems. Data extraction and analysis of the relevant literature within the last five years (2018-2022) are compared to answer the set research questions, and the results show the prevalence of approximate methods and hybrid approaches.
Article
Computer Science, Interdisciplinary Applications
Mehmet Erdem, Cagri Koc, Eda Yucel
Summary: This paper presents an electric home health care routing and scheduling problem, aiming to minimize the total cost while providing services to patients. By developing an adaptive large neighborhood search heuristic and tailoring it to the specific features of the problem, the paper achieves highly efficient solutions. The study quantifies the advantages of considering different charger technologies and shows that downgrading job competence levels can improve the total cost.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Gaurav Srivastava, Alok Singh, Rammohan Mallipeddi
Summary: This paper proposes a nondominated sorting genetic algorithm II approach to address the vehicle routing problem with time windows, known for its multiobjective characteristics. The performance of this approach is evaluated on standard benchmark instances, showing its superiority over the state-of-the-art approach for the problem.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Payakorn Saksuriya, Chulin Likasiri
Summary: This work presents a heuristic approach for solving vehicle routing problems with time windows (VRPTW) incorporating compatibility constraints. The proposed heuristic combines local search, ruin and recreate procedure, and particle swarm optimization to efficiently find optimal solutions. Experimental results demonstrate the effectiveness of the heuristic in solving benchmark instances and instances with compatibility constraints.
APPLIED SCIENCES-BASEL
(2022)
Article
Green & Sustainable Science & Technology
Yong Wang, Jingxin Zhou, Yaoyao Sun, Xiuwen Wang, Jiayi Zhe, Haizhong Wang
Summary: This study introduces a problem involving the optimization of electric vehicle charging station locations and routes, considering time windows and resource sharing. A bi-objective programming model and a hybrid algorithm are proposed to solve the problem, and an empirical study is conducted in Chongqing City, China. The results demonstrate the effectiveness and practicality of the proposed solution method in achieving sustainable operations.
Review
Computer Science, Artificial Intelligence
Binghai Zhou, Zhe Zhao
Summary: This paper proposes a multi-objective optimization algorithm to solve the electric vehicle routing problem with battery swap consideration and time windows constraints. Experimental results show that this algorithm outperforms other algorithms in terms of solution quality and convergence rate.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Biqin Hu, Bin Yang, Wei Jiang, Zhe Yang, Mohammed Abdella Kemal
Summary: In common logistic activities involving storage and distribution, challenges like urban traffic congestion and restricted parking can be alleviated by setting arrival times for customer orders within time windows. This study proposes a dual-objective optimization approach that links time windows with distribution efficiency, aiming to minimize total costs while meeting time constraints. Investigating various intelligent algorithms, the squirrel search algorithm (SSA) demonstrates more stable performance and superior solution outcomes.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Vinicius Martins Santos Gandra, Hatice Calik, Tony Wauters, Tulio A. M. Toffolo, Marco Antonio M. Carvalho, Greet Vanden Berghe
Summary: The paper introduces a generalized 2E-LRP with two-dimensional loading restrictions (2E-LRP2L) and evaluates its performance using a heuristic optimization method combined with different loading strategies on real-world data. The proposed method is compared against state-of-the-art 2E-LRP methods on benchmark instances, showing that it is highly competitive and able to find most best-known solutions as well as providing some new ones.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Gaurav Srivastava, Alok Singh
Summary: This paper addresses a variant of the vehicle routing problem with time windows and proposes two evolutionary approaches to maximize the quality of service delivered to the customer. The proposed approaches incorporate various heuristics and provide better initial solutions compared to random solutions. Experimental results show that the proposed approaches outperform the state-of-the-art approach in terms of solution quality and execution time. (c) 2022 Elsevier B.V. All rights reserved.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Information Systems
Xiaoshu Xiang, Ye Tian, Ran Cheng, Xingyi Zhang, Shengxiang Yang, Yaochu Jin
Summary: This study proposes a benchmark generator for online dynamic single-objective and multi-objective optimization problems. It adjusts the influence of solutions found in each environment on the problems in the next environment through different types of functions and predefined parameters, and suggests a test suite consisting of continuous and discrete online dynamic optimization problems. The proposed OL-DOP test suite exhibits time-deception compared to existing benchmark test suites and evaluates the ability of dynamic optimization algorithms to tackle the influence of solutions on successive environment problems.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
M. Salehi Sarbijan, J. Behnamian
Summary: This paper introduces the real-time collaborative feeder vehicle routing problem (RTCFVRP) with flexible time windows and proposes algorithms including mixed-integer linear programming, multi-objective particle swarm optimization (MOPSO), and MOPSO-variable neighborhood search (MOPSO-VNS) to solve the problem. The results show that the proposed algorithm outperforms other algorithms in both static and dynamic modes.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Economics
Luigi Moccia, Gilbert Laporte
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2016)
Article
Economics
Luigi Moccia, Giovanni Giallombardo, Gilbert Laporte
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2017)
Article
Computer Science, Interdisciplinary Applications
Luigi Moccia, Jean-Francois Cordeau, Maria Flavia Monaco, Marcello Sammarra
COMPUTERS & OPERATIONS RESEARCH
(2009)
Article
Management
Jean-Francois Cordeau, Gilbert Laporte, Luigi Moccia, Gregorio Sorrentino
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2011)
Article
Computer Science, Information Systems
Luigi Moccia
Article
Operations Research & Management Science
M. Gaudioso, L. Moccia, M. F. Monaco
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
(2010)
Article
Management
L. Moccia, J-F Cordeau, G. Laporte
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2012)
Article
Computer Science, Hardware & Architecture
Luigi Moccia, Jean-Francois Cordeau, Gilbert Laporte, Stefan Ropke, Maria Pia Valentini
Article
Economics
Giovanni Giallombardo, Luigi Moccia, Matteo Salani, Ilaria Vacca
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2010)
Article
Computer Science, Information Systems
Antonella Guzzo, Luigi Moccia, Domenico Sacca, Edoardo Serra
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2013)
Article
Transportation Science & Technology
Luigi Moccia, Duncan W. Allen, Gilbert Laporte, Andrea Spinosa
Summary: The research investigates the impact of fully automated metro lines on semi-rapid transit modes, showing improvements in user experience and cost savings. It highlights how the low marginal cost of automation can benefit both users and operators in terms of reduced waiting times and operating expenses.
Article
Transportation Science & Technology
Luigi Moccia, Duncan W. Allen, Gilbert Laporte
Article
Transportation Science & Technology
Luigi Moccia, Duncan W. Allen, Eric C. Bruun
Article
Computer Science, Interdisciplinary Applications
Gabriel Gutierrez-Jarpa, Gilbert Laporte, Vladimir Marianov, Luigi Moccia
COMPUTERS & OPERATIONS RESEARCH
(2017)
Article
Economics
Songyot Kitthamkesorn, Anthony Chen, Seungkyu Ryu, Sathaporn Opasanon
Summary: The study introduces a new mathematical model to determine the optimal location of park-and-ride facilities, addressing the limitations of traditional models and considering factors such as route similarity and user heterogeneity.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2024)
