Process Integration and Optimization for Sustainability, Год журнала: 2025, Номер unknown
Опубликована: Май 8, 2025
Язык: Английский
Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 122200 - 122200
Опубликована: Окт. 23, 2023
Язык: Английский
Процитировано
135
Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown
Опубликована: Янв. 3, 2025
Язык: Английский
Процитировано
5
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
16
Knowledge-Based Systems, Год журнала: 2024, Номер 302, С. 112347 - 112347
Опубликована: Авг. 5, 2024
Язык: Английский
Процитировано
14
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
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
Sustainable Computing Informatics and Systems, Год журнала: 2025, Номер unknown, С. 101096 - 101096
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
2
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
2
Building and Environment, Год журнала: 2024, Номер 250, С. 111185 - 111185
Опубликована: Янв. 10, 2024
Язык: Английский
Процитировано
8
IEEE Access, Год журнала: 2024, Номер 12, С. 122377 - 122400
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
7