Logistics Center Location Research Articles

Lead Battery Reverse Logistics Center Location Model and Simulation Analysis Based on Genetic Algorithm and Greedy Algorithm

Lead Battery Reverse Logistics Center Location Model and Simulation Analysis Based on Genetic Algorithm and Greedy Algorithm

Research on Location Optimization of Logistics Center Based on Center of Gravity Method: A Case Study of Jilin Province

With the rapid development of the global economy, logistics plays an increasingly important role in modern society. As the core node of the logistics system, logistics center is responsible for the distribution, transfer and distribution of goods. The scientific and rational location of the logistics center will directly affect the efficiency and cost of logistics transportation. In this paper, Jilin Province, a key agricultural producing area in China, is selected as the research object. By collecting certain historical data information, regression analysis method and moving average method are used to predict the grain output of each city, and the average value of the predicted values obtained by the two methods is used as the final forecast value. The initial site selection of grain logistics center in Jilin Province is calculated by using the center of gravity, and the new site selection after iteration is obtained by using the center of gravity. Finally, the location of the final grain logistics center is determined by considering the factors such as geographical location, traffic accessibility and usable area around. This study can provide some reference value for the optimization of logistics center location.

Enhancing Logistics Optimization

With the expansion of the logistics network, enterprise logistics distribution faces increasing challenges, including high transportation costs, low distribution efficiency, and unstable distribution networks. To address these issues, this study focuses on optimizing enterprise logistics distribution using a double-layer (DL) model. In this paper, we propose a DL model for optimizing enterprise logistics distribution. The DL model is designed to find the optimal solution using the particle swarm optimization (PSO) algorithm. By leveraging location data from the region, the DL model evaluates and compares alternative distribution centers to determine the most efficient distribution strategy. The results demonstrate that the DL site selection model developed in this study effectively addresses the tasks of logistics center location and distribution optimization among alternative distribution centers. Comparison tests reveal that the distribution path proposed by the DL model is more accessible and cost-effective compared to alternative approaches.

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

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.

Совершенствование транспортных технологических процессов железнодорожной сети

Purpose: To increase the efficiency of the railway transport network through the mutually beneficial interaction of lines of various categories. Methods: Methods of control theory, system analysis, synthesis and mathematical modeling were used. Results: The tools for determining the optimal location of logistics centers using the center of gravity method have been improved by taking into account the criteria for minimizing transport costs, category, specialization and social significance of the line, as well as determining the weight values of the criteria using the hierarchy analysis method. Practical significance: The proposed tools allow you to determine the location of the logistics center at the intersection of intensive and lowintensity railway lines, taking into account the criteria for minimizing transport costs, the specialization of the line and the social significance of the lines for the regions under consideration.

Aptenodytes forsteri optimization algorithm for low-carbon logistics network under demand uncertainty.

As China's "double carbon" goal continues to advance, logistics as a key area of carbon emissions and low-carbon logistics center site selection are key links in the process. However, existing studies on logistics center location often ignore the impact of demand uncertainty, which leads to a waste of resources in the planning and construction processes. We take logistics cost and carbon emission as the objectives, and the multi-objective site selection model established based on stochastic programming theory takes demand uncertainty as a stochastic constraint. We transform the stochastic constraint model into a 0-1 mixed integer multi-objective planning model by utilizing the idea of equivalence transformation. The Aptenodytes Forsteri Optimization (AFO) algorithm is combined with the Ideal Point Method to solve the model, and the algorithm is compared with the Particle Swarm Optimization (PSO), Differential Evolutionary (DE), Tabu Search (TS), Sparrow Search (SS) algorithms, and the exact solver Linear Interactive and General Optimizer (LINGO). The examples verify the validity of the models and algorithms, with an average reduction of 6.2% and 3.6% in logistics costs and carbon emissions in the case of demand determination, and at the confidence level of 0.9 under demand uncertainty, both logistics costs and carbon emissions are decreased to varying degrees. This study provides a new research idea for the low-carbon logistics location problem under demand uncertainty, which helps to promote the transformation of the logistics industry to low-carbon and high-efficiency.

考虑不同投资模式的城市群绿色物流中心选址模型

考虑不同投资模式的城市群绿色物流中心选址模型

Ensemble decision making for logistics center location

Ensemble decision making for logistics center location

Optimizing Logistics Center Location in Brčko District: A Fuzzy Approach Analysis

Optimizing Logistics Center Location in Brčko District: A Fuzzy Approach Analysis

DETERMINATION OF LOGISTICS PARAMETERS OF E-CARGO BIKES FOR SUSTAINABLE DELIVERY OF POSTAL CARGO IN CITIES

The article is devoted to formation of parameters of logistics system of cargo transportation using «green technologies». The feasibility of using a distribution center with certain parameters of the supply chain is assessed. The solution of the problem of choosing the location of the logistics center was solved simultaneously with solving the problem of routing and choosing the carrying capacity of the vehicle. The number and configuration of transportation routes depends on the volume of cargo delivery, the location of the consignor and consignees, as well as on the carrying capacity of vehicles. Each location of the distribution center determines the number of routes, the distance of transportation, the volume of traffic on each section of the routes. As a result, it was proposed to use the value of the transport work of rolling stock as an indicator that takes into account these components. The initial data for determining the effective location of the distribution center is the volume of traffic for each sender and the location of consumers. In connection with the current trends in the development of "green technologies" in urban logistics, the question of the feasibility of using freight electric bicycles at the proposed location of the city logistics center was considered. When using green technology, electric cargo bicycles were considered as vehicles. The solution to the problem of determining the most efficient distribution center was carried out taking into account the possible carrying capacity of electric bicycles. A number of bicycles with different carrying capacities that can be used to transport mail cargo were selected. It was revealed that the rational location of the distribution center ensures minimal transport work during the transportation of goods to any carrying capacity of the bicycle. To assess the effectiveness of an electric cargo bike, the amount of transport work performed using a battery capacity unit was used as a criterion. The value of this criterion is determined by the technical characteristics of the bike, namely carrying capacity, mileage on a single battery charge and battery capacity. The value of the efficiency criterion determined the ranks of bicycles taking into account technological parameters. Keywords: logistics center, electric bike, distribution center, efficiency, supply, green technology.

A Proposal for Selecting a Logistics Center Location Suitable for Multimodal Transport: Turkey Practice

Lojistik günümüzde hemen hemen her alanda etkili olup gerek zamandan tasarruf gerekse maddi kazanç sağlamada büyük rol oynamaktadır. Aktif bir lojistik merkez için altyapının yanı sıra konum da önemlidir. Büyük yatırımlarla yapılan lojistik merkezlerden kısa sürede kâr sağlamak için mümkün olan en iyi konumu belirlemek gerekmektedir. Lojistik merkezin konumu belirlenirken birçok değerlendirme yapılmaktadır. Bu çalışmada ülkemizdeki lojistik merkezlerde çok modlu taşımacılığı daha etkin hale getirebilmek için demiryolu, liman ve havaalanı bağlantısı olan iller Coğrafi Bilgi Sistemi (CBS) ile seçilmiştir. Ekonomik canlılığın artması için ise ‘Dış Ticaret (ithalat ve ihracat miktarları)’, ‘Organize Sanayi Bölgeleri’, ‘Tarımsal Organize Sanayi Bölgeleri’ ve ‘Sınır Kapıları’ kriterleri belirlenmiş ve bu kriterler lojistik alanında uzman kişilerin görüşlerine göre değerlendirilmiştir. CBS’de senaryolara göre elde edilen iller bu değerlendirme sonuçları ve kriterlerin ilgili kurumlardan alınan illere ait verileri doğrultusunda en uygun lojistik merkez konumu için AHP tekniği kullanılarak sıralanmıştır.

The Selection of Logistics Center Location Based on AHP-TOPSIS Method: A Study on Çukurova Region

Bu çalışmada, Çukurova bölgesinde lojistik merkezi olmaya en uygun yer veya yerlerin tespit edilmesi amaçlanmıştır. Bu çalışma kapsamında ele alınan aday şehirler Çok Kriterli Karar Verme (ÇKKV) teknikleri arasında en çok tercih edilen Analytic Hierarchy Process (AHP) ve Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) yöntemlerine dayalı olarak değerlendirilmiştir. Kriterlerin belirlenmesinde ilgili alan yazın taranmış, lojistik alanında uzman 4 kişinin görüşlerine başvurulmuştur. AHP yöntemi ile kriter ağırlıkları hesaplanmış ve alternatiflerin tercih sıralaması TOPSIS yöntemi ile yapılmıştır. Analiz sonuçlarına göre, Adana alternatifinin Çukurova bölgesinde lojistik merkezi olmaya aday en uygun yer olduğu tespit edilmiştir. Ayrıca, sıralamada Mersin ve Hatay aday şehirlerinin birbirine çok yakın değerler aldığı ancak Hatay şehrinin, Mersin’e kıyasla daha iyi değere sahip olduğu saptanmıştır.

Pharmaceutical Logistics Center Location in the Context of Centralized Medicine Procurement: A Literature Review

Pharmaceutical Logistics Center Location in the Context of Centralized Medicine Procurement: A Literature Review

Research on emergency logistics location-routing problem for public health emergencies

At present, the world's public health emergencies are becoming more and more frequent, bringing great threats to people's life and health safety and economic development. In the new crown pneumonia epidemic that affected the world in 2020, due to the shortage of medical resources and poor transportation of materials, the comprehensive control of the epidemic encountered great difficulties. In order to minimize the impact and loss caused by public health emergencies, it is necessary to study the location of emergency logistics centers and transportation route planning. This paper studies the positioning-routing problem in the emergency logistics system after public health emergencies, applies genetic algorithm and the Traveling Salesman Problem (TSP) to solve the positioning-routing problem in this paper, takes the current Wuhan map as an example, combines the p-center theory to take the location of each new coronary pneumonia directional receiving hospital as the basis for determining the material distribution center and transportation route, and uses actual cases to study the positioning-route problem.

Evaluating the Effects of Logistics Center Location: An Analytical Framework for Sustainable Urban Logistics

Sustainable urban logistics require support of sustainable logistics center location planning. Nevertheless, urban public authorities generally experience difficulties in choosing a successful planning scheme, due to the lack of a rigorous analytical tool designed to help understand how logistics center location affects sustainability throughout the supply chain. A poor location can keep a firm or a supply chain from reaching its economic, environmental, and social sustainability goals. A good location can help meet these goals. To address the pressing cause of policy failure, this paper developed an analytical framework by integrating the multi-criteria decision-making method and the shortest path model with multiple objectives. The developed framework can be used to evaluate the effects of logistics center location schemes on travel time, transport costs, carbon emission, and road traffic, and further explore the conflict level among them. It is applied to Beijing in this paper. The analysis results reveal that: (1) travel time, transport costs, and carbon emissions all vary along with the distance from logistics center location to the city center; (2) encouraging cargo companies to plan their truck paths with the navigation objective of minimizing travel time is an excellent way to achieve sustainable urban logistics, because in this scenario, freight transport is the quickest, and transport costs and carbon emissions are all more moderate. Additionally, this paper confirmed the conflict level among sustainability goals of urban logistics based on actual contextual data. The proposed framework is a helpful guide tool for urban planners to develop sustainable logistics land-use planning and responsive policy interventions.

Application of the Analytical Hierarchy Process (AHP) Method in Selecting Warehouse Locations for Onlineshop Goods Storage (Case Study: Expedited Shipment of Finished Goods)

Storage of finished goods is one of the important factors needed by a company, both offline and online manufacturing. The problem that often occurs is the lack of area and inadequate warehouse locations for storing finished goods. This problem is also found in the activities of storing finished goods in shipping expeditions. The condition of the warehouse which was initially less efficient was due to the location of the warehouse being less spacious, the absence of safety equipment and also areas prone to flooding. The goal to be achieved is to choose the optimal warehouse location from several existing alternatives. The method used is the Analytical Hierarchy Process (AHP) method to develop a hierarchy of logistics center location selection. Research variables using criteria include distance, cost, facilities, geographical position and warehouse area. The results of data processing produce the highest criterion weight value of 0.3228, namely the area of ​​the warehouse and the smallest criterion weight of 0.0417, namely the cost criterion. In addition, the highest value of the work alternative is 0.4085 on the SPILL warehousing alternative and the smallest value is 0.2749 on the Rungkut Industri alternative.

AHP Application for Logistics Center Location Selection According to Criteria

Today, logistics is effective in every field and has an important share in the revival of both domestic and foreign trade. The rapid increase in competition in global trade has increased the importance of the logistics sector and, accordingly, logistics centers. With well-planned and high-performance logistics centers in our country, the contribution of the logistics sector to the economy will increase and it will be ensured that our country is a logistics base in international transportation corridors. In this study, Criteria were determined conducting a comprehensive literature review for logistics center location These criteria consist of seven main criteria, namely population, economy, cost, socio-economic status, infrastructure, geographical location and service, and twenty-seven sub-criteria belonging to these main criteria. The criterias were evaluated by benefiting from the opinions of experts in the field of logistics, and the order of importance of the main and sub-criteria determined for the logistics center location determination was found by AHP methods.

Конфигурирование терминально-складской инфраструктуры транспортного узла на основе развития метода экономико-географического разграничения грузопотоков

Purpose: To formulate proposals for configuring terminal-warehouse infrastructure for the placement of storage facilities inside a transport hub. Methods: Basing on the analysis of pub-lications in the trend of the research data, optimization geometric Euclidean model of freight process, embodied on the territory of a transport hub, was applied to find optimal cargo flow distribution by dividing the flow into parts representing “influence areas”. Results: optimiza-tion algorithm for freight process was developed in the article on the basis of classical integral calculus methods, the algorithm allows to discover those ones among many distributive center possible locations which allows in view of restriction complex to determine “influence area” of distributive center with the largest area in comparison with the initial area. Practical signifi-cance: Economic effect was obtained from base rental rate reduction that is due to possible change of logistic freight distribution center location outside dense urban development territo-ry where base rental rate is higher.

An Improved Sparrow Search Algorithm for Location Optimization of Logistics Distribution Centers

In modern society where business development is booming, it is of great importance to investigate location optimization of logistics distribution centers. In order to achieve greater efficiency of distribution system, save the distribution costs and the construction cost of logistics distribution center, good point set method and decreasing nonlinear inertia weight are proposed to improve sparrow search algorithm (SSA) to solve the mathematical model for logistics distribution center location. First, in order to prevent SSA falling in local optimal, while improving the convergence speed and efficiency of SSA, good point set method and decreasing nonlinear inertia weight are applied to improve the SSA. The test results of eight benchmark functions show that the fitness value and convergence speed of the proposed ISSA are smaller and faster. Second, compared with SSA, WOSA and PSO, the ISSA has the lowest total cost for solving the mathematical model of logistics distribution center.

A distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability

Logistics center location optimization is one of the core issues in the study of logistics networks. A sensible logistics center distribution can improve the efficiency of goods transportation and the operation efficiency of logistics enterprises. In this paper, we study the problem of optimizing the location of logistics distribution centers in logistics networks with the objective of minimizing the operating costs of logistics distribution centers. Then, we presents a distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability. Firstly, the future goods quantity prediction data of each node is obtained through the grey-residual Markov chain prediction model. Then, a logistics center location optimization model with three node expansion mechanisms is developed with the objective of minimizing the objective function. Finally, by using the forecast data of goods demand obtained by the grey-residual Markov chain prediction method, we conducted simulation experiments on the cost-minimizing logistics center location optimization model under three different node expansion methods. The corresponding simulation results are obtained by particle swarm optimization algorithm to prove the effectiveness of the model.