Article
Computer Science, Interdisciplinary Applications
Farouq Halawa, Sreenath Chalil Madathil, Mohammad T. Khasawneh
Summary: A proposed non-linear multi-objective model utilizing Genetic Algorithm is effective in optimizing outpatient clinic design by maximizing natural daylight exposure and minimizing total walking distance for patients. Efficient algorithms are identified to tackle challenges in computational complexity and area constraints approximation for spaces with wide bounds in clinic design. Sensitive analysis reveals that the main factors affecting algorithm performance are the selection mechanism for best Pareto points, number of spaces requiring lighting, and lighting dataset used, with adapted Genetic Algorithm proving superior in achieving better results for a multi-objective problem compared to other optimization algorithms.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Management
Jake Weiner, Andreas T. Ernst, Xiaodong Li, Yuan Sun, Kalyanmoy Deb
Summary: This paper introduces a new heuristic algorithm, LaPSO, which combines Lagrangian Relaxation and Particle Swarm Optimization, and incorporates a new repair heuristic called Largest Violation Perturbation (LVP) to solve the Maximum Edge Disjoint Paths (MEDP) problem. LaPSO outperforms both state-of-the-art heuristic methods and standard MIP solvers, demonstrating superior heuristic solutions and strong bounds within limited runtimes.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Manoj Kumar, Aryabartta Sahu, Pinaki Mitra
Summary: Although metaheuristics provide only approximate solutions in feasible time and may take considerable time for very large instances, utilizing highly parallel metaheuristics on modern GPUs can further reduce execution time. It is interesting to determine the best metaheuristic for each problem type since they are not problem-specific. This study evaluates the performance of different metaheuristics for the quadratic assignment problem using a massively parallel machine like a GPU.
APPLIED SOFT COMPUTING
(2021)
Article
Management
Pamela C. Nolz, Nabil Absi, Dominique Feillet, Clovis Seragiotto
Summary: This paper addresses a consistent vehicle routing problem for the delivery of parcels using electric vehicles. The problem considers the constraint that vehicles can only be charged between delivery and pickup tours, and aims to generate efficient vehicle routes while optimizing multiple objectives.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Industrial
Javier Alcaraz, Laura Anton-Sanchez, Francisco Saldanha-da-Gama
Summary: This work provides new insights on bi-criteria resource-constrained project scheduling problems. It presents a realistic problem definition and optimization model, followed by the development of an algorithm and a metaheuristic algorithm to solve the problem.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Aslihan Karas, Feristah Ozcelik
Summary: This study introduces the Assembly Line Worker Assignment and Rebalancing Problem (ALWARBP), aiming to minimize variability in cycle time and workstation assignments by reallocating tasks and workers after disruptions occur. Both methods successfully obtained optimal solutions in small instances, while the proposed ABC algorithm showed better performance in terms of solution value and computation time in large test instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Management
Jinjia Huang, Chung-Piaw Teo, Fan Wang, Zhou Xu
Summary: In resource scheduling problems, maintaining appropriate buffer between successive services can effectively reduce crossings and conflicts. This study provides a theoretical explanation of the advantages of buffering approach from the perspective of robust optimization and demonstrates that the buffering method can minimize the worst-case number of conflicts under down-monotone uncertainty sets.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Zhi Lu, Anna Martinez-Gavara, Jin-Kao Hao, Xiangjing Lai
Summary: This study addresses the capacitated dispersion problem in a weighted graph and proposes an effective and parameter-free heuristic algorithm based on solution-based tabu search. The algorithm employs a fast greedy construction heuristic and utilizes hash functions to identify eligible candidate solutions.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Ana Camila Perez, Eduardo Sanchez-Ansola, Alejandro Rosete, Omar Rojas, Guillermo Sosa-Gomez
Summary: This study applies the partial evaluation approach to the School Bus Routing Problem (SBRP) in order to reduce its execution time. By analyzing the changed routes, unnecessary re-evaluation can be avoided, leading to a significant reduction in execution time. The results demonstrate that execution time can be decreased in 80% of instances, with an average reduction of 73.6%.
Article
Management
Juanjo Peiro, Iris Jimenez, Jose Laguardia, Rafael Marti
Summary: This paper investigates the adaptation of GRASP and VND methodologies to the capacitated dispersion problem, proposing a hybrid algorithm within the strategic oscillation framework. Extensive experimentation and mathematical modeling are used to evaluate the algorithm's performance. Comparisons with existing software solutions are also made.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Yun-Chia Liang, Yen-Yu Lin, Angela Hsiang-Ling Chen, Wei-Sheng Chen
Summary: This research used the 2016 MLB season as a case study and proposed the Variable Neighborhood Search algorithm with different coding structures to optimize sports scheduling. The algorithm successfully reduced the total travelling distances of all teams in the league, showing promising performance in real-world cases.
Article
Operations Research & Management Science
Stephane Grandcolas, Cyril Pain-Barre
Summary: This paper presents a hybrid metaheuristic approach called PVS for the two-dimensional strip packing problem, which relies on a local search algorithm and an exact procedure. PVS follows a specific anytime strategy to continuously improve the current solution until it is provably optimal or reaches a given time limit. Experimental results show that the method is competitive on moderate-sized instances.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Aram M. Ahmed, Tarik A. Rashid, Soran Ab M. Saeed
Summary: This paper introduces a powerful swarm intelligence optimization algorithm named Dynamic Cat Swarm Optimization, which addresses the issue of premature convergence by modifying the existing Cat Swarm Optimization algorithm. Experimental results demonstrate the algorithm's outperformance compared to several well-known algorithms, further confirmed through statistical methods and graphs.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Jose Garcia, Carlos Maureira
Summary: In this work, a hybrid algorithm incorporating the k-nearest neighbor technique was evaluated to enhance the results of a quantum cuckoo search algorithm for resource allocation. Experimental results demonstrate the significant contribution of the k-nearest neighbor technique to the final solutions, showing that the hybrid algorithm consistently outperforms state-of-the-art algorithms in most analyzed instances.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Mohamed Abdel-Basset, Reda Mohamed, Ibrahim M. Hezam, Karam M. Sallam, Ahmad M. Alshamrani, Ibrahim A. Hameed
Summary: This paper adapts several recently published metaheuristic algorithms to optimize the NP-hard problem of decision and resource allocation in mobile edge computing enabled blockchain networks. Different encoding schemes are used to represent the mining decisions, transmission power, and computing resources of the miners, and three algorithm variants are proposed for optimization.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
