A two-echelon location routing problem considering sustainability and hybrid open and closed routes under uncertainty

Hajghani, Masoud; Forghani, Mohammad Ali; Heidari, Ali; Khalilzadeh, Mohammad; Kebriyaii, Omid

doi:10.1016/j.heliyon.2023.e14258

Cited by 13 publications

(6 citation statements)

References 56 publications

(59 reference statements)

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“…The diversity index measures the length of the cube diameter of the space that is used by the final target values for the set of unsatisfactory solutions, as calculated in equation (27). The greater value the better (Jolai et al ., 2013; Hajghani et al ., 2023). Spacing…”

Section: Computational Resultsmentioning

confidence: 99%

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Zahedi

Kia

Khalilzadeh³

2023

JAMR

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PurposeThe vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development.Design/methodology/approachIn this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS).FindingsThe results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis.Originality/valueIn this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.

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Section: Computational Resultsmentioning

confidence: 99%

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Zahedi

Kia

Khalilzadeh³

2023

JAMR

Self Cite

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“…The formula (19) is the objective function indicating that the carbon cost of the transportation process is minimized; The formula (20) indicates that the vehicle arrives at a customer and must leave from that customer; The formula (21) indicates the flow balance; The formula (22) indicates that each customer can be served by one vehicle; and the formula (23) indicates the maximum load limit.…”

Section: Distribution Path Optimization Modelmentioning

confidence: 99%

Optimized Design of Multi-Level Low-Carbon Logistics Distribution Scheme Based on Two Stages

Fu,

Yue,

Yan

2024

AoT

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The logistics network, as a key component of commodity distribution, has a direct impact on carbon emissions and resource utilization. Its main objective is to optimize the distribution process of commodities in order to improve efficiency, reduce costs, ensure timely delivery of commodities, and simultaneously satisfy customers' needs. The problem of multiple factors in the optimal allocation of logistics network objectives leading to decision-making difficulties is addressed. The complex multilevel logistics network optimization problem is decomposed into two stages. The first stage determines the selection of cargo transit points and the distribution of cargo flow between nodes, starting with the establishment of a Comprehensive Modal Emission Model (CMEM) taking into account the speed of the vehicle, the amount of cargo loaded, the road surface conditions and the characteristics of the vehicle itself. Secondly, the carbon emission cost generated from the flow of goods, together with the transportation cost, distribution cost and fixed cost at the transit point, constitute the comprehensive cost, and establish a multi-objective optimization model of low-carbon logistics network with the goal of minimizing the comprehensive cost and transportation time. The Non-dominated Sorted Genetic Algorithm with Elite Strategies (NSGA-II) is used for the solution. Finally, MATLAB software was used to numerically analyze the two schemes of "Considering Carbon Tax Levy" and "Not Considering Carbon Tax Levy". The results show that the government's imposition of an environmental tax on companies will change the distribution of transit points and flows within the logistics network, reducing CO2 emissions by 226.5 kg and saving 257.65 CNY in comprehensive costs. The second stage determines the order and path of distribution from each transit point to its own customers, establishes a low-carbon logistics network distribution path optimization model with the goal of minimizing the cost of carbon emissions, and solves the problem using Genetic Algorithm (GA). Through the coordinated use of the two-stage optimization model, it provides enterprises with a network distribution solution that takes into account the low-carbon goal and logistics efficiency, and provides the government with a basis for carbon tax levy and a reference for the tax rate.

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“…A hybrid heuristic algorithm combining neighborhood search (NS) and Tabu search (TS) algorithms is introduced to solve the presented model. Hajghani et al, [13] a MILP model including minimization of costs and CO2 emissions and maximization of social responsibility (creating job opportunities and community development) was developed for the problem. The proposed model seeks to minimize the total costs by reducing the use of vehicles through reducing the number of transportation routes in the two-echelon distribution network (due to the incurred fixed cost of transportation per vehicle) and increasing the allowable load of vehicles.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Yadegari,

Molana,

Kashan

et al. 2024

Decis. Mak. Appl. Manag. Eng.

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

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A two-echelon location routing problem considering sustainability and hybrid open and closed routes under uncertainty

Cited by 13 publications

References 56 publications

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Optimized Design of Multi-Level Low-Carbon Logistics Distribution Scheme Based on Two Stages

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

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