Clustering Analysis and Time Series Approaches for Effective Resource Allocation and Route Planning in Managing Confirmed Cases DOI

Y.F. Chen,

Hsieh-Chih Hsu, Shih‐Hsiung Lee

и другие.

Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 19 - 31

Опубликована: Янв. 1, 2025

Язык: Английский

Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications DOI
Weiguo Zhao, Liying Wang, Zhenxing Zhang

и другие.

Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 122200 - 122200

Опубликована: Окт. 23, 2023

Язык: Английский

Процитировано

132

Advances in Sand Cat Swarm Optimization: A Comprehensive Study DOI

Ferzat Anka,

Nazim Aghayev

Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 3, 2025

Язык: Английский

Процитировано

5

WOA: Wombat Optimization Algorithm for Solving Supply Chain Optimization Problems DOI Creative Commons
Zoubida Benmamoun,

Khaoula Khlie,

Mohammad Dehghani

и другие.

Mathematics, Год журнала: 2024, Номер 12(7), С. 1059 - 1059

Опубликована: Апрель 1, 2024

Supply Chain (SC) Optimization is a key activity in today’s industry with the goal of increasing operational efficiency, reducing costs, and improving customer satisfaction. Traditional optimization methods often struggle to effectively use resources while handling complex dynamic chain networks. This paper introduces novel biomimetic metaheuristic algorithm called Wombat Algorithm (WOA) for supply optimization. replicates natural behaviors observed wombats living wild, particularly focusing on their foraging tactics evasive maneuvers towards predators. The theory WOA described then mathematically modeled two phases: (i) exploration based simulation wombat movements during trying find food (ii) exploitation simulating when diving nearby tunnels defend against its effectiveness addressing challenges assessed by CEC 2017 test suite across various problem dimensions, including 10, 30, 50, 100. findings indicate that demonstrates strong ability manage exploitation, maintains balance between them throughout search phase deliver optimal solutions problems. A total twelve well-known algorithms are upon performance process. outcomes simulations reveal outperforms other algorithms, achieving superior results most benchmark functions securing top ranking as efficient optimizer. Using Wilcoxon rank sum statistical analysis, it has been proven significantly. put twenty-two constrained problems from 2011 four engineering design showcase solve real-world demonstrate excels applications delivering outperforming competitors.

Язык: Английский

Процитировано

14

An improved Genghis Khan optimizer based on enhanced solution quality strategy for global optimization and feature selection problems DOI
Mahmoud Abdel-Salam, Ahmed Ibrahim Alzahrani,

Fahad Alblehai

и другие.

Knowledge-Based Systems, Год журнала: 2024, Номер 302, С. 112347 - 112347

Опубликована: Авг. 5, 2024

Язык: Английский

Процитировано

14

A recent review of solution approaches for green vehicle routing problem and its variants DOI Creative Commons
Annisa Kesy Garside, Noor Azurati Ahmad, Mohd Nabil Muhtazaruddin

и другие.

Operations Research Perspectives, Год журнала: 2024, Номер 12, С. 100303 - 100303

Опубликована: Апрель 28, 2024

The green vehicle routing problem (GVRP) has been a prominent topic in the literature on logistics and transportation, leading to extensive research previous review studies covering various aspects. Operations seen development of exact approximation approaches for different extensions GVRP. This paper presents an up-to-date thorough GVRP spanning from 2016 2023, encompassing 458 papers. significant contribution lies updated solution algorithms applied both single-objective multi-objective Notably, 92.58% papers introduced mathematical model GVRP, with many researchers adopting mixed integer linear programming as preferred modeling approach. findings indicate that metaheuristics hybrid are most employed addressing Among approaches, combination metaheuristics-metaheuristics is particularly favored by researchers. Furthermore, large neighborhood search (LNS) its variants (especially adaptive search) emerges widely adopted algorithm These proposed within metaheuristic where A-/LNS often combined other algorithms. Conversely, predominant NSGA-II being frequently algorithm. Researchers utilize GAMS CPLEX optimization software solvers. MATLAB commonly language implementing

Язык: Английский

Процитировано

11

Multi-objective Optimization for Green Delivery Routing Problems with Flexible Time Windows DOI Creative Commons
Burak Gülmez, Michael Emmerich, Yingjie Fan

и другие.

Applied Artificial Intelligence, Год журнала: 2024, Номер 38(1)

Опубликована: Март 27, 2024

This paper presents a model and heuristic solution algorithms for the Green Vehicle Routing Problem with Flexible Time Windows. A scenario of new vehicle routing is analyzed in which customers are asked to provide alternative time windows offer flexibility help route planners find more fuel-efficient routes ("green delivery"). Customers can rank their preferred as first, second, third. The optimization aims reduce tour costs, promote electromobility over fossil fuels, such diesel, meet customer preferences when possible affordable. study incorporates multi-objective three objectives, overall cost, use fuel, satisfaction. For problem, set realistic benchmark problems created four mainstream solvers applied Pareto front approximation: NSGA-II, NSGA-III, MOEA/D, SMS-EMOA. These compared terms effectiveness achieving objectives minimizing travel promoting electromobility, meeting preferences. uses five different single-vehicle planning. Two major findings that selection metaheuristic make big difference algorithm performance. resulting 3-D fronts reveal nature this class problems: Interestingly, flexible windows, most users still be delivered only small concessions other objectives. However, using one window per user lead an increasingly drastic cost fuel consumption.

Язык: Английский

Процитировано

10

Novel Sustainable Green Transportation: A Neutrosophic Multi-Objective Model Considering Various Factors in Logistics DOI

Kalaivani Kaspar,

K. Palanivel

Sustainable Computing Informatics and Systems, Год журнала: 2025, Номер unknown, С. 101096 - 101096

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2

Collaboration and Resource Sharing for the Multi-Depot Electric Vehicle Routing Problem with Time Windows and Dynamic Customer Demands DOI Open Access
Yong Wang, Can Chen,

Yuanhan Wei

и другие.

Sustainability, Год журнала: 2025, Номер 17(6), С. 2700 - 2700

Опубликована: Март 18, 2025

With increasingly diverse customer demands and the rapid growth of new energy logistics industry, establishing a sustainable responsive network is critical. In multi-depot network, adopting collaborative distribution resource sharing can significantly improve operational efficiency. This study proposes collaboration for electric vehicle (EV) routing problem with time windows dynamic demands. A bi-objective optimization model formulated to minimize total operating costs number EVs. To solve model, novel hybrid algorithm combining mini-batch k-means clustering an improved multi-objective differential evolutionary (IMODE) proposed. integrates genetic operations non-dominated sorting operation enhance solution quality. The strategies dynamically inserting charging stations are embedded within identify Pareto-optimal solutions effectively. algorithm’s efficacy applicability verified through comparisons algorithm, particle swarm ant colony optimization, tabu search. Additionally, case company in Chongqing City, China demonstrates that proposed method reduces improves Sensitivity analysis considering different demand response modes provides insights reducing enhancing findings offer essential promoting environmentally resource-efficient city.

Язык: Английский

Процитировано

1

A multi-objective optimization method for enclosed-space lighting design based on MOPSO DOI
Xian Zhang,

Jingluan Wang,

Yao Zhou

и другие.

Building and Environment, Год журнала: 2024, Номер 250, С. 111185 - 111185

Опубликована: Янв. 10, 2024

Язык: Английский

Процитировано

7

Identifying and Understanding Student Dropouts Using Metaheuristic Optimized Classifiers and Explainable Artificial Intelligence Techniques DOI Creative Commons
Goran Radic, Luka Jovanovic, Nebojša Bačanin

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 122377 - 122400

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

7