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
Engineering, Industrial
Luka Matijevic
Summary: This paper studies the Electric Vehicle Routing Problem with time-dependent speeds and soft time windows. The authors formulated a Mixed Integer Linear Program (MILP) and developed a General Variable Neighborhood Search (GVNS) metaheuristic to tackle the problem. Experimental results showed that GVNS can find better quality solutions in less time compared to other methods.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2023)
Article
Chemistry, Multidisciplinary
Christina Iliopoulou, Ioannis Tassopoulos, Grigorios Beligiannis
Summary: This study develops a VNS-based algorithm for the transit route network design problem (TRNDP). The algorithm is compared with some recent and efficient methods, and the results show that it outperforms existing implementations in short computational times.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Interdisciplinary Applications
Stefan Voigt, Markus Frank, Pirmin Fontaine, Heinrich Kuhn
Summary: This article examines three variants of the vehicle routing problem and proposes a unified solution approach based on hybrid adaptive large neighborhood search. Experimental results demonstrate the competitive performance and superior robustness of this approach.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Mostafa Hajiaghaei-Keshteli, Golman Rahmanifar, Mostafa Mohammadi, Fatemeh Gholian-Jouybari, Jirf Jaromfr Klemes, Sasan Zahmatkesh, Awais Bokhari, Gaetano Fusco, Chiara Colombaroni
Summary: This paper proposes a mixed integer linear mathematical model to optimize the multi-period production routing problem using electric vehicles. The model considers the cost of utilizing electric vehicles, mileage limitations, and the impact of traffic conditions on energy consumption. It also introduces a simultaneous multi-period dynamic production routing problem using heterogeneous electric vehicles.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Management
David Wolfinger, Margaretha Gansterer, Karlf. Doerner, Nikolas Popper
Summary: This article addresses the logistics problem in COVID-19 testing, introduces the contagious disease testing problem (CDTP), and presents a solution. By optimizing the opening of test centers and routes of mobile test teams to minimize costs, the efficiency of public health response to pandemics can be improved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Gen-Han Wu, Chen -Yang Cheng, Pourya Pourhejazy, Bai-Lyn Fang
Summary: Major corporations compete over the strengths of their supply chains. This study proposes a new method based on mixed-integer linear programming to solve the production scheduling and routing problem by integrating machine scheduling with vehicle routing. Extensive numerical experiments show that the developed hybrid metaheuristics are effective in solving this problem.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Bruno Salezze Vieira, Glaydston Mattos Ribeiro, Laura Bahiense
Summary: This paper proposes two metaheuristic algorithms to solve a complex problem in the automotive industry called the Heterogeneous Site-Dependent Multi-depot Multi-trip Periodic Vehicle Routing Problem (HSDMDMTPVRP). The experimental results show that both algorithms perform well, finding many new best-known solutions and achieving close results to the known best solutions.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Israel Pereira Souza, Maria Claudia Silva Boeres, Renato Elias Nunes Moraes
Summary: In this paper, a hybrid algorithm based on a discrete adaptation of the Differential Evolution metaheuristic combined with local search procedures is proposed to solve the Capacitated Vehicle Routing Problem (CVRP). The proposed algorithm, CDELS, shows significantly better results compared to state-of-the-art methods with a confidence level of 99% based on computational experiments on six classical datasets.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
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
Economics
Meng Yang, Yaodong Ni, Qinyu Song
Summary: This paper investigates the problem of constructing routes over multiple days while maintaining driver consistency. It introduces a new quantitative measure of driver consistency and models the problem considering uncertainties in customer demands, travel times, and service times. A hybrid algorithm is proposed to solve the NP-hard problem. Computational experiments are conducted to evaluate the performance of the proposed approach and analyze the trade-off between total travel time and driver consistency.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Engineering, Multidisciplinary
Arjun Paul, Ravi Shankar Kumar, Chayanika Rout, Adrijit Goswami
Summary: This research addresses a real-life multi-depot and multi-period vehicle routing problem with time window constraints, aiming to minimize the total distance traveled by the fleet over the planning horizon. A hybrid meta-heuristic approach combining tabu search and variable neighbourhood search algorithms is proposed to optimize the problem. Numerical experiments are conducted to demonstrate the efficacy of the proposed method and mathematical formulation across instances of varying scales from small to large.
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES
(2021)
Article
Engineering, Industrial
Esmaeil Akhondi Bajegani, Naser Mollaverdi, Mahdi Alinaghian
Summary: This paper introduces a mathematical model for solving vehicle routing problems and designs two heuristic algorithms to tackle the NP-hard nature of the problem. Experimental results indicate the superior performance of the mat-heuristic algorithm, and a case study demonstrates its effectiveness in reducing vehicle travel time.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(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
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
Management
Krzysztof Fleszar
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2017)
Article
Management
Krzysztof Fleszar, Khalil S. Hindi
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2018)
Article
Computer Science, Interdisciplinary Applications
Krzysztof Fleszar, Khalil S. Hindi
COMPUTERS & OPERATIONS RESEARCH
(2009)
Article
Computer Science, Interdisciplinary Applications
Christoforos Charalambous, Krzysztof Fleszar
COMPUTERS & OPERATIONS RESEARCH
(2011)
Article
Computer Science, Interdisciplinary Applications
Krzysztof Fleszar
COMPUTERS & OPERATIONS RESEARCH
(2013)
Article
Management
K. Fleszar, K. S. Hindi
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2008)
Article
Management
Krzysztof Fleszar, Christoforos Charalambous
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2011)
Article
Computer Science, Artificial Intelligence
Christoforos Charalambous, Krzysztof Fleszar
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
(2012)
Article
Computer Science, Artificial Intelligence
Krzysztof Fleszar, Christoforos Charalambous, Khalil S. Hindi
JOURNAL OF INTELLIGENT MANUFACTURING
(2012)
Article
Management
Krzysztof Fleszar
Summary: The study introduces a new branch-and-bound algorithm for the Quadratic Multiple Knapsack Problem, which utilizes a new upper bound and local search to optimize solutions, achieving better performance in terms of computational time and solution quality compared to previous algorithms.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Krzysztof Fleszar
Summary: The BPPC-IF problem is a variant of the classic bin packing problem where fragments of the same item can be packed in different bins and some items cannot be packed together. To solve this problem, a new MILP model and two heuristics have been proposed, and computational experiments show their performance advantages on benchmark instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Krzysztof Fleszar
Summary: VSBPPTW is a variant of the classical bin packing problem that minimizes the cost of using different sized bins to pack all items, while ensuring time-compatibility between the items in each bin. A new MILP model is proposed to address VSBPPTW, which fills each bin with items from a maximal time-compatible set and uses a compressed network flow formulation. New fast heuristics are also introduced to improve the solution quality.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Krzysztof Fleszar
INFORMS JOURNAL ON COMPUTING
(2016)
Article
Computer Science, Interdisciplinary Applications
KS Hindi, K Fleszar
COMPUTERS & INDUSTRIAL ENGINEERING
(2004)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)