Article
Computer Science, Interdisciplinary Applications
Vahid Riahi, M. A. Hakim Newton, Abdul Sattar
Summary: Time-dependent prize-collecting arc routing problems (TD-PARPs) generalize regular prize-collecting arc routing problems by allowing travel times to vary, taking into account real-life uncertain factors such as traffic and weather conditions. In this research, deterministic heuristic search algorithms and a meta-heuristic based scatter search (SS) algorithm are proposed for solving TD-PARPs. The experimental results on benchmark problems show that the SS algorithm outperforms existing methods significantly.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Daniel Negrotto, Irene Loiseau
Summary: The Capacitated location routing problem (CLRP) combines the features of the capacitated facility location problem (CFLP) and the multiple depots vehicle routing problem (MDVRP), with the main goal of minimizing total costs while satisfying vehicle and depot capacity constraints. The prize-collecting capacitated location routing problem (PC-CLRP) is a new variant of CLRP that aims to maximize overall benefits by allowing certain customers to remain unvisited and providing gains for visited customers.
Article
Computer Science, Interdisciplinary Applications
Stefan Bock, Nils Boysen
Summary: Many online retailers use scattered storage in their picking areas, which increases the likelihood of products being located in close proximity, making picking more efficient. However, replenishment workers face additional effort due to the need to travel along multiple shelves for restocking. The special parallel-aisle structure in warehouses allows for an exact solution algorithm with pseudo-polynomial runtime, resulting in significant performance gains for an optimized stowing process.
INFORMS JOURNAL ON COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Serkan Kaya
Summary: The issue of managing waste in rapidly growing urban areas has been a major problem for local administrations. One of the most critical issues in waste management is the collection and transportation of solid waste, which are both costly and difficult to address. This study addresses the problem of collecting waste in a district in the province of Sanliurfa. To solve the problem in question, it proposes a hybrid firefly and particle swarm optimization algorithm developed using local search. The results revealed that the proposed algorithm provided 31% better outcomes than those obtained in the real-life case, 10% better than those of the geographic information system, and 5% better than those of a linear programming model.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Lu Han, Changjun Wang, Dachuan Xu, Dongmei Zhang
Summary: This paper studies the prize-collecting $k$-Steiner tree problem and proposes two approximation algorithms with improved approximation ratios.
TSINGHUA SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Resmi RamachandranPillai, Michael Arock
Summary: The paper introduces a new variant of vehicle routing problem that combines improved algorithm and neural systems, proposing spiking neural firefly optimization to solve dynamic VRP. By working in parallel across multiple neural systems, the proposed method has made significant progress in finding optimal solutions.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Management
David Whittle, Marcus Brazil, Peter A. Grossman, J. Hyam Rubinstein, Doreen A. Thomas
Summary: The PCEST problem is a generalization of the EST problem, where the solution connects a subset of given points to maximize the net value of the network. The algorithmic framework includes efficient methods for determining subsets of points that must be in every solution, subsets of points that cannot be in any solution, and methods for generating and concatenating full Steiner trees.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Software Engineering
Luana Souza Almeida, Alireza Ghasemi, Floris Goerlandt
Summary: MPC-ARCP is an optimization problem that aims to determine the roads to unblock for reconnecting isolated communities after a natural disaster. E-ARCP is a software designed to solve MPC-ARCP and display network results, with great potential for reuse in network repair and restoration research.
Review
Green & Sustainable Science & Technology
Reza Moghdani, Khodakaram Salimifard, Emrah Demir, Abdelkader Benyettou
Summary: In recent decades, optimization packages have been increasingly utilized for efficient management of distribution systems, resulting in significant savings in global transportation costs. The emerging research field of green vehicle routing problem (GVRP) draws attention from many researchers. Findings suggest that researches on GVRPs are relatively new and there is room for significant improvements in various areas.
JOURNAL OF CLEANER PRODUCTION
(2021)
Review
Green & Sustainable Science & Technology
Reza Moghdani, Khodakaram Salimifard, Emrah Demir, Abdelkader Benyettou
Summary: In recent decades, the utilization of optimization packages in distribution systems based on Operations Research and Mathematical Programming techniques has increased significantly, leading to substantial savings in global transportation costs. The emerging research field of Green Vehicle Routing Problem (GVRP) attracts many researchers, with plenty of room for improvement in various areas.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Economics
Carlos Brunner, Ricardo Giesen, Mathias A. Klapp, Luz Florez-Calderon
Summary: In logistics operations in cities with significant road grades, we studied a VRP model considering road grade and vehicle load, achieving up to a 12.4% reduction in operating costs. Our routing plans prioritize roads with smaller grades initially and plan higher grades after unloading cargo. We also found that inserting intermediate depot visits and splitting routes into subroutes can be cheaper when traveling over mountainous areas with a lighter vehicle.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2021)
Article
Energy & Fuels
Dimitra Trachanatzi, Manousos Rigakis, Magdalene Marinaki, Yannis Marinakis
Summary: The research introduces a new variant of the Vehicle Routing Problem, the E-PCVRP, which aims to maximize collected prizes, minimize costs, and reduce CO2 emissions through a load-distance function. The Teaching-Learning-Based Optimization (TLBO) algorithm is utilized for solving this problem, incorporating a heuristic encoding/decoding technique for a discrete representation.
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
(2021)
Article
Computer Science, Artificial Intelligence
J. Behnamian, M. Ghadimi, M. Farajiamiri
Summary: The importance of green vehicle routing lies in the unsustainable nature of current distribution systems and the lack of consideration for environmental impacts. This study presents a mathematical formulation for a green heterogeneous vehicle routing problem and develops a firefly algorithm to solve it. The use of data mining significantly improves the algorithm's performance.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Management
Simona Mancini, Margaretha Gansterer, Richard F. Hartl
Summary: The logistics industry faces fierce competition, prompting companies to focus more on economic efficiency. Incomplete resource utilization is a major source of inefficiency, but better resource utilization can be achieved through carrier collaborations. The study examines a multi-period collaborative vehicle routing problem, emphasizing the importance of time and service consistency as well as workload balance.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Industrial
Julian Baals
Summary: Freight transportation, including JIT supplier networks, contributes significantly to global CO2 emissions. The recent literature discusses the JIT truck routing problem (TRP-JIT), which involves multiple suppliers serving a single OEM with the logistics provider organizing the milk-run routes. This study focuses on the environmental impact of TRP-JIT by considering weight-distance and using a bi-criterial LNS method to estimate Pareto frontiers.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Dimitra Trachanatzi, Manousos Rigakis, Magdalene Marinaki, Yannis Marinakis, Nikolaos Matsatsinis
Article
Computer Science, Artificial Intelligence
Manousos Rigakis, Dimitra Trachanatzi, Magdalene Marinaki, Yannis Marinakis
Summary: This research focuses on generating tourist trip itineraries for a group with different individual preferences, proposing the n-person Prize-Collecting Vehicle Routing Problem and using a combination of game theory and metaheuristic methods to solve it. By configuring a set of locations to be visited beforehand and employing the metaheuristic firefly algorithm to determine tourist routes, the proposed approach generates efficient and satisfactory tourist trip itineraries for heterogeneous groups.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Nikolaos A. Kyriakakis, Magdalene Marinaki, Yannis Marinakis
Summary: Two swarm intelligence algorithms for the Cumulative Capacitated Vehicle Routing Problem were implemented, with one of them achieving new best known solutions for two instances and reaching best known solutions in 92 out of 112 tested instances. The effectiveness of the algorithms was compared to other approaches in the literature.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
A. Nikolaos Kyriakakis, Magdalene Marinaki, Nikolaos Matsatsinis, Yannis Marinakis
Summary: This paper introduces a novel dynamic optimization problem, Moving Peak Drone Search Problem (MPDSP), and proposes a multi-swarm framework to solve it. By testing seven optimization algorithms, it is found that Particle Swarm Optimization implementations are the most effective for solving the problem.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Dimitra Trachanatzi, Manousos Rigakis, Andromachi Taxidou, Magdalene Marinaki, Yannis Marinakis, Nikolaos Matsatsinis
LEARNING AND INTELLIGENT OPTIMIZATION, LION
(2020)
Article
Computer Science, Artificial Intelligence
Dimitra Trachanatzi, Manousos Rigakis, Magdalene Marinaki, Yannis Marinakis
EXPERT SYSTEMS WITH APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Guiliang Gong, Jiuqiang Tang, Dan Huang, Qiang Luo, Kaikai Zhu, Ningtao Peng
Summary: This paper proposes a flexible job shop scheduling problem with discrete operation sequence flexibility and designs an improved memetic algorithm to solve it. Experimental results show that the algorithm outperforms other algorithms in terms of performance. The proposed model and algorithm can help production managers obtain optimal scheduling schemes considering operations with or without sequence constraints.
SWARM AND EVOLUTIONARY COMPUTATION
(2024)
Article
Computer Science, Artificial Intelligence
Daniel Molina-Perez, Efren Mezura-Montes, Edgar Alfredo Portilla-Flores, Eduardo Vega-Alvarado, Barbara Calva-Yanez
Summary: This paper presents a new proposal based on two fundamental strategies to improve the performance of the differential evolution algorithm when solving MINLP problems. The proposal considers a set of good fitness-infeasible solutions to explore promising regions and introduces a composite trial vector generation method to enhance combinatorial exploration and convergence capacity.
SWARM AND EVOLUTIONARY COMPUTATION
(2024)