Optimization of Location-Routing for Multi-Vehicle Combinations with Capacity Constraints Based on Binary Equilibrium Optimizers

The Location-Routing Problem (LRP) becomes a more intricate subject when the limits of capacities of vehicles and warehouses are considered, which is an NP-hard problem. Moreover, as the number of vehicles increases, the solution to LRP is exacerbated because of the complexity of transportation and...

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Veröffentlicht in:Axioms Jg. 13; H. 1; S. 31
Hauptverfasser: Xi, Rui, Lv, Danju, Yu, Yueyun, Huang, Xin, Wang, Ziqian, Gu, Lianglian, Zhu, Zhicheng, Zhang, Yan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.01.2024
Schlagworte:
Algorithms
Assembly
binary swarm intelligent optimization algorithm
Case studies
Decision making
decision space construction
Design
Empirical analysis
equilibrium optimizer algorithm
Heuristic
Integer programming
Linear programming
location-routing optimization
Logistics
Mathematical optimization
Mathematical research
Medical research
Mixed integer
mixed-integer linear programming
Optimization
Route optimization
Site selection
Sums
Systems design
Trucks
Vehicle routing
Vehicles
Warehouses
China
ISSN:2075-1680, 2075-1680
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Zusammenfassung:The Location-Routing Problem (LRP) becomes a more intricate subject when the limits of capacities of vehicles and warehouses are considered, which is an NP-hard problem. Moreover, as the number of vehicles increases, the solution to LRP is exacerbated because of the complexity of transportation and the combination of routes. To solve the problem, this paper proposed a Discrete Assembly Combination-Delivery (DACA) strategy based on, the Binary Equilibrium Optimizer (BiEO) algorithm, in addition, this paper also proposes a mixed-integer linear programming model for the problem of this paper. Our primary objective is to address both the route optimization problem and the assembly group sum problem concurrently. Our BiEO algorithm was designed as discrete in decision space to meet the requirements of the LRP represented by the DACA strategy catering to the multi-vehicle LRP scenario. The efficacy of the BiEO algorithm with the DACA strategy is demonstrated. through empirical analysis utilizing authentic data from Changchun City, China, Remarkably, the experiments reveal that the BiEO algorithm outperforms conventional methods, specifically GA, PSO, and DE algorithms, resulting in reduced costs. Notably, the results show the DACA strategy enables the simultaneous optimization of the LRP and the vehicle routing problem (VRP), ultimately leading to cost reduction. This innovative algorithm proficiently tackles both the assembly group sum and route optimization problems intrinsic to multi-level LRP instances.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms13010031