Collaboration and Resource Sharing for the Multi-Depot Electric Vehicle Routing Problem with Time Windows and Dynamic Customer Demands

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2700 - 2700

Published: March 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.

Language: Английский

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Dynamic Routing in Urban Logistics: A Comprehensive Review of AI, Real-Time Data, and Sustainability Impacts

Sinergi International Journal of Logistics, Journal Year: 2025, Volume and Issue: 3(2), P. 68 - 79

Published: April 23, 2025

This paper examines the impact of dynamic routing algorithms on urban logistics, focusing their role in improving operational efficiency and environmental sustainability. With rise e-commerce increasing complexity transport networks, has emerged as a critical solution for reducing delivery times, optimizing fleet usage, minimizing emissions. The methodology this review involved comprehensive search key academic databases, including Scopus, IEEE Xplore, Google Scholar, using relevant keywords inclusion criteria. results demonstrate that integrating real-time data, artificial intelligence, hybrid optimization models significantly enhance decisions. Furthermore, systems incorporate GIS IoT data enable more responsive context-aware logistics operations. However, challenges such infrastructure disparities, interoperability, policy support must be addressed to fully realize potential environments. study concludes by emphasizing importance interventions collaborative efforts overcome these barriers proposes future research directions improve scalability integration systems.

Language: Английский

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Optimizing Supply Chain Efficiency using Innovative Goal Programming and Advanced Metaheuristic Techniques

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(16), P. 7151 - 7151

Published: Aug. 14, 2024

This paper presents an optimization approach for supply chain management that incorporates goal programming (GP), dependent chance constraints (DCC), and the hunger games search algorithm (HGSA). The model acknowledges uncertainty by embedding uncertain parameters promote resilience efficiency. It focuses on minimizing costs while maximizing on-time deliveries optimizing key decision variables such as production setups, quantities, inventory levels, backorders. Extensive simulations numerical results confirm model’s effectiveness in providing robust solutions to dynamically changing problems when compared conventional models. However, integrated introduces substantial computational complexity, which may pose challenges large-scale real-world applications. Additionally, reliance precise probabilistic fuzzy limit its applicability environments with insufficient or imprecise data. Despite these limitations, proposed has potential significantly enhance efficiency, offering valuable insights both academia industry.

Language: Английский

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The Multi-Depot Traveling Purchaser Problem with Shared Resources

Sustainability, Journal Year: 2022, Volume and Issue: 14(16), P. 10190 - 10190

Published: Aug. 17, 2022

Using shared resources has created better opportunities in the field of sustainable logistics and procurement. The Multi-Depot Traveling Purchaser Problem under Shared Resources (MDTPPSR) is a new variant (TPP) inbound logistics. In this problem, each depot can purchase its products using other depots, vehicles do not have to return their starting depots. routing problem Multi-Trip, Open Vehicle Routing Problem. A tailored integer programming model formulated minimize total purchasers’ costs. Considering complexity model, we presented decomposition-based algorithm that breaks down into two phases. first phase, tactical decisions regarding supplier selection type collaboration are made. second sequence visiting determined. To amend made these phases, heuristic algorithms based on removing insertion operators also proposed. experimental results show only purchasing reduce cost by up 29.11%, but it decreases number dispatched most instances.

Language: Английский

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Multi-Objective Intercity Carpooling Route Optimization Considering Carbon Emission

Sustainability, Journal Year: 2023, Volume and Issue: 15(3), P. 2261 - 2261

Published: Jan. 26, 2023

In recent years, intercity carpooling has been vigorously developed in China. Considering the differences between and intracity carpooling, this paper first defines path optimization problem with time window. Based on balance of interests among passengers, platform, government, a multi-objective function is constructed to minimize passenger cost, maximize platform revenue, carbon emission vehicle capacity, boarding alighting points, service, other constraints. Secondly, order further improve coordination ability search speed operator, uses particle swarm algorithm help operator remember previous position iterative information, designs PSO (Particle Swarm Optimization) improved NSGA-II (Non-dominated Sorting Genetic Algorithm) solve model. Finally, feasibility model verified by numerical analysis Xi’an–Xianyang carpool. The results show that 1 5-8-O-D-16-13, 2 7-3-6-O-D-15-11-14, 3 2-1-4-O-D-12-10-9. Compared algorithm, PSO-NSGA-II designed significant advantages global convergence speed.

Language: Английский

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AN ALGORITHM FOR GARBAGE TRUCK ROUTING IN CITIES WITH A FIXATION ON CONTAINER FILLING LEVEL

Transport Problems, Journal Year: 2023, Volume and Issue: 18(1), P. 75 - 87

Published: March 1, 2023

An algorithm for optimizing the routes of a set vehicles used collection and removal municipal solid waste in metropolis is proposed. The eliminates problem applying heuristic methods multi-agent optimization, which NP non-deterministic polynomial-time-hard. application leads to guaranteed exact solution. Through restrictions on carrying capacity vehicles, size input matrix representing transport network can be reduced an adequate size. This process uses statistical information about filling levels container bins. applied example two megacities. shortest are built different numbers points (from 12 72) route. dependence total mileage number involved studied.

Language: Английский

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Smart Navigation for Vehicles to Avoid Road Traffic Congestion using Weighted Adaptive Navigation * Search Algorithm

International Journal of Electronics and Communication Engineering, Journal Year: 2023, Volume and Issue: 10(5), P. 170 - 177

Published: May 31, 2023

The innovative route navigation system is designed to provide better accuracy in finding the optimal routes for efficient navigation. By leveraging real-time traffic data and incorporating a Weighted Adaptive Navigation * search Algorithm, aims minimize user travel time congestion. algorithm analyzes road network, considering conditions, capacities, other relevant parameters determine best users. Find path based on both distance congestion factors. provides step-by-step directions estimated times each segment, assisting users efficiently navigating avoiding congested areas. has significantly improved by 98% routes. It redirect it into shortest reach destination turn-by-turn direction. achieves predictions successfully guides through less paths, reducing improving overall experience.

Language: Английский

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Designing a Fuzzy Mathematical Model for a Two-Echelon Allocation-Routing Problem by Applying Route Conditions: A New Interactive Fuzzy Approach

Decision Making Applications in Management and Engineering, Journal Year: 2024, Volume and Issue: 7(2), P. 172 - 196

Published: Feb. 20, 2024

In vehicle routing problems (VRP), the optimal allocation of transportation by considering factors such as route hardness, driver experience and worn-out has a significant effect on costs reduction approaching real-world conditions. this paper, novel fuzzy mixed integer non-linear mathematical model to address two-echelon allocation-routing problem under uncertainty is proposed applying fleet The cost allocating drivers diverse vehicles computed at first echelon problem, type, wear-out, experience. Additionally, different routes are defused with varying levels hardness. goal second improve reliability defining within each section. To solve model, Torabi Hessini (TH), Selimi Ozkarahan (SO) methods, newly approach (PIA) were utilized transform multi-objective into single-objective one. Numerical tests performance indicators used validate effectiveness both solution method. validation computation results indicate that outperforms TH SO approaches.

Language: Английский

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Scenario-Based Multi-Objective Location-Routing Model for Pre-Disaster Planning: A Philippine Case Study

Sustainability, Journal Year: 2023, Volume and Issue: 15(6), P. 4882 - 4882

Published: March 9, 2023

The demand for humanitarian supply chains grows daily as the incidence of calamities rises. Typhoons cause thousands casualties each year. As a result, policymakers and governmental authorities must develop effective readiness response measures part pre-disaster plans. This paper proposed stochastic model multi-objective location-routing creating network response. aims to minimize overall costs network’s setup, time required travel through it, number vehicles necessary transferring affected individuals evacuation centers. concentrates on scenarios in uncertainty. provided was implemented an actual scenario one Philippines’ provinces solved using Multi-Objective Particle Swarm Optimization (MOPSO), which is also contrasted with Simulated Annealing (MOSA) ε-constraint approach. According empirical findings, can be used identify distribution hubs centers choose best routes unexpected disaster scenarios. Given that ideal number, location, capacity DCs ECs are known advance, government decision-makers solve any potential shortages problems during disaster.

Language: Английский

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Minimising Last-Mile Delivery Cost and Vehicle Usage Through an Optimised Delivery Network Considering Customer-Preferred Time Windows

Published: June 29, 2023

In the dynamic and developing e-commerce era, last-mile delivery has emerged as one of critical operations among all. The in industry is facing high costs due to a going economic crisis which led fuel other operating cost increments. To overcome this situation, needs optimise vehicle routing based on time windows minimise overall cost. Despite numerous studies delivery, there paucity optimisation considering customer's anticipated windows. Therefore, study been conducted with objective optimising minimising transportation usage while meeting some practical requirements such variety package types, compatibility different types vehicles; customer expected heterogeneous fleet vehicles. After careful literature review, paper introduces mathematical model delivery. proposed was simulated SupplyChainGuru® modelling simulation software. concluded that minimised by about 22% reducing number vehicles route, failed count utilising maximum possible capacity also increasing satisfaction giving consumers chance select preferred for This cluster-based will improve logistic supply chain serve platform extending process industries well.

Language: Английский

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