Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method

As society continues to age, people are becoming more concerned about their health care. This has led to an increase in the demand for medical products in urban areas, emphasizing the need for regular and prompt deliveries. However, the existing logistics centers are located in the suburbs of Seoul, a metropolitan city, which makes it challenging to ensure timely delivery. To address this issue, this study aims to establish new logistics centers in urban areas, particularly in Seoul, while minimizing CO2 emissions from delivery vehicles in alignment with sustainability efforts. The scientific gap addressed in and the novelty of this paper is that the input parameters are prepared based on actual data from a medical company in Korea to reflect reality, and the mathematical model-based optimization technique is applied to determine the optimal location of a new logistics center. The genetic algorithm is developed to solve the proposed mathematical model by deriving optimal or near-optimal solutions. Furthermore, the numerical experiment examined the impact of establishing a new logistics center in one of the candidate areas of local governments in Seoul by considering environmental impact. As a result, the new logistics network can reduce CO2 emissions by approximately 66.74% compared to the existing logistics network.

Section: Literature Reviewmentioning

confidence: 99%

“…Equation (9) prevents vehicles from moving between the same nodes. Equation (10) indicates that vehicles should depart from the logistics center. Equation (11) indicates that vehicles can deliver only one route in each delivery sequence.…”

Section: Mathematical Modelmentioning

confidence: 99%

Efficient Expansion Algorithm of Urban Logistics Network for Medical Products Considering Environmental Impact

Jo,

Ko,

et al. 2024

“…Constraints ( 6) and (7) ensure that when a vehicle leaves the DCs for a retailer, it eventually returns to the starting point. Constraint (8) guarantees that each retailer is served by only one vehicle for each product in each period. Constraint (9) implies that whenever a vehicle arrives at a retailer location, it must leave again.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…The LIRP model involves the integrated optimization of facility location, inventory management, and routing arrangement within the supply chain network. This integration tackles the logistics LIRP, which poses a comprehensive optimization challenge for the entire logistics system [8]. The purpose of this study is to provide an optimized solution for supply chain managers or practitioners, empowering them to efficiently manage the PPSCN and achieve cost effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Perishable Product Supply Chain Network Using Hybrid Metaheuristic Algorithms

Li-hong

Shan

2023

This paper focuses on optimizing the long- and short-term planning of the perishable product supply chain network (PPSCN). It addresses the integration of strategic location, tactical inventory, and operational routing decisions. Additionally, it takes into consideration the specific characteristics of perishable products, including their shelf life, inventory management, and transportation damages. The main objective is to minimize the overall supply chain cost. To achieve this, a nonlinear mixed integer programming model is developed for the multi-echelon, multi-product, and multi-period location-inventory-routing problem (LIRP) in the PPSCN. Two hybrid metaheuristic algorithms, namely genetic algorithm (GA) and multiple population genetic algorithm (MPGA), are hybridized with variable neighborhood search (VNS) and proposed to solve this NP-hard problem. Moreover, a novel coding method is devised to represent the complex structure of the LIRP problem. The input parameters are tuned using the Taguchi experimental design method, considering the sensitivity of meta-heuristic algorithms to these parameters. Through experiments of various scales, the hybrid MPGA with VNS indicates superior performance, as evidenced by the experimental results. Sensitivity analysis is conducted to examine the influence of key model parameters on the optimal objective, providing valuable management implications. The results clearly validate the efficacy of the proposed model and solution method as a reliable tool for optimizing the design problem of the PPSCN.

“…The score of visiting function is different depending on the time of charging. The location-inventoryrouting problem (LIRP) is a common LRP that is based on a multi-stage demand forecasting model [33] and contains five parts of total logistics costs: the costs of trunk transportation and regional transportation, the fixed costs of distribution center construction, the inventory holding costs, shortage costs, and salvage, which are conflicting and are difficult to be optimized. This makes the issue of pickup and delivery of electric vehicles more complex [34].…”

Section: Literature Reviewmentioning

confidence: 99%

An Artificial Physarum polycephalum Colony for the Electric Location-Routing Problem

Cai,

Wang,

et al. 2023

Electric vehicles invented for environmental sustainability are prone to adverse impacts on environmental sustainability due to the location and construction of their charging facilities. In this article, an artificial Physarum polycephalum colony is proposed to solve the novel challenging problem. First, the electric location-routing problem is established as a multi-objective network panning model with electric constraints to provide the optimal charging infrastructure layout, electric vehicle maintenance costs, and traffic conditions. The electric facility location problem and vehicle routing problem are integrated by integer programming, which considers the total distance, total time, total cost, total number of electric vehicles, and order fill rate. Second, an artificial Physarum polycephalum colony is introduced to solve the complex electric location-routing problem and includes the two basic operations of expansion and contraction. In the expansion operation, the optimal parent individuals will generate more offspring individuals, so as to expand the population size. In the contraction operation, only individuals with high fitness will be selected to survive through a merge sorting algorithm, resulting in a decrease in population size to the initial value. Through the iterative computing of the two main operations, the proposed artificial Physarum polycephalum colony can finally find the optimal solution to the objective function. Third, a benchmark test is designed for the electric location-routing problem by extracting the real road network from Tokyo, and the experimental results prove the effectiveness and applicability of this work.