Distribution Center Location Research Articles

Integrasi Metode Gravitasi dan Metode Perbandingan Eksponensial untuk Penentuan Pusat Distribusi Pangan di Kabupaten Halmahera Selatan

AbstractThis study aims to determine the location of distribution centers in each islandgroup in South Halmahera Regency. Data sources were obtained from survey resultsand literature studies. Integration of Gravity Models and Exponential ComparisonMethods are used to determine the best location. Subdistrict of Kayoa as the locationof distribution centers for Kayoa-Makian islands group, Subdistrict of West Gane forGane islands group, Subdistrict of Bacan for Bacan-Kasiruta islands group, and theObi Subdistrict for Obi Islands group. The location chosen as the distribution centerin each island group is a main subdistrict which physically has better resourcecarrying capacity.

Solving the location problem of front distribution center for omni-channel retailing

Consumer demand and retailing models nowadays are being upgraded more frequently. More and more retailers are switching to the Omni-channel retailing model. Choosing a reasonable location for a front distribution center (FDC) helps control an enterprise's cost and improves its service level. This is especially true in the existence of fierce competition. In this paper, two important and contradictory objectives are proposed for the first time in the FDC location problem: minimizing the distribution costs from the facility and minimizing the fixed cost of the facility's location. For these objectives, a bi-objective programming model is established by considering the factors of a facility's capacity, demand and rent fluctuation. Meanwhile, the FDC location problem has been solved by compromising programming and elite set multi-objective simulated annealing algorithm respectively. Taking the FDC locations set of an e-commerce enterprise in a region of Beijing as an empirical sample, this paper uses the above algorithms to re-plan the FDC locations of the enterprise. This algorithm provides support for retail enterprises by helping find the best FDC location. Based on the empirical results, some comments and future research directions are also proposed.

Location optimization of a competitive distribution center for urban cold chain logistics in terms of low-carbon emissions

Owing to the fast economic and social development in Wuhan, the demand for cold chain logistics is increasing rapidly. Currently, the scale of the existing distribution centers cannot fully meet this demand, so building new ones would seem necessary. Research rarely considers consumer choice from the perspective of competition between new and existing cold chain distribution centers, and the low-carbon concept is rarely considered when a competitive site is selected. This paper therefore puts forward a model to assist the decision-making process regarding the choice of location where cold chain logistics facilities might be sited. Based on a bi-level programming method, this model is constructed where the upper level of government aims to determine an optimal location and scale for a cold chain distribution center as well as a rational trading policy regarding carbon emissions to minimize the total social cost of the whole logistics system. The lower level adopts the demand user equilibrium model, which considers the demands of logistics users when choosing between new and existing cold chain distribution centers, so as to minimize the cost incurred by each logistics user. We use the cloud particle swarm optimization algorithm to solve the model and decide a suitable location for a new center in Wuhan, the principal city in the Hubei Province, in China. The study reveals that: (1) The high demand is equivalent to the high number of new distribution centers; (2) The high attractiveness of these centers is equal to their high total scale; (3) Changes in carbon emissions trading prices have an impact on the scale, total carbon emissions, and total social cost of new cold chain distribution centers; (4) The carbon emissions quota policy has an impact on the scale of the location chosen for a new cold chain distribution center, total carbon emissions, and total social costs. This article provides a scientific basis regarding decisions concerning the location of new cold chain distribution centers by the government, and provides some ideas for energy conservation improvement and carbon emissions reduction by the whole society.

Multi-objective model for the location of distribution centres with cost evaluation, road access and insecurity

This paper presents an alternative to the location of distribution centres considering a multi-objective model minimising insecurity cost and road access for a case study in the City of Barranquilla (Colombia). For the solution of the model, 15 different scenarios of variation of the importance of the proposed objectives are considered. As a basis for the design of the modelling, the characterisation and classification of the variables with the highest incidence in the location of distribution centres or warehouses are posed. It is possible to demonstrate the impact of the evaluation and analysis of the mathematical model for the location of this type of facility.

Location Model of Fresh Agricultural Products Logistics Distribution Center Based on Network Nodes

The high logistics cost of fresh produce is the main problem that restricts the distribution of produce. How to reduce the logistics cost of fresh agricultural products, improve the utilization rate of logistics facilities, and improve distribution efficiency and service levels has become the key to research. As an important hub for fresh agricultural products, the fresh agricultural product distribution center can effectively integrate supply and demand information and is the key to ensuring the efficiency of fresh agricultural product distribution, especially to meet the urban fresh agricultural product distribution needs. The fresh agricultural product urban logistics distribution center has the characteristics of small service radius, small scale, many distribution batches and high distribution frequency. The service radius and the scale of the distribution center determine the function of the distribution service. In order to save costs while ensuring distribution efficiency and logistics service levels, it is necessary to scientifically and rationally plan the location of urban distribution centers for fresh agricultural products. Despite extensive research on the location of logistics distribution centers, there are still some shortcomings. First, by analyzing and summarizing the existing literature, the theory and research methods of urban logistics distribution centers for fresh agricultural products are summarized, the characteristics of urban logistics distribution centers for fresh agricultural products are analyzed, and the status of logistics centers for fresh agricultural products is summarized. Influencing factors and site selection process introduced the basic principles and steps of immune algorithm. Secondly, based on the location theory of distribution centers, a cost model for the location of urban logistics distribution centers for fresh agricultural products is established. The model takes into account economic and social factors, including distribution costs, fixed costs, operating costs, waste costs and carbon emission costs. In the case of traffic congestion, a carbon emission factor is introduced to calculate the environmental cost of the allocation process. Finally, combined with the calculation steps of the immune algorithm, the solution steps are designed for the location model of the urban fresh agricultural products logistics distribution center, and the actual calculation examples are studied using MATLAB software programming, and the distribution center is obtained based on the low model. Through the method of this article, the transportation speed of fresh agricultural products logistics distribution center location has been increased by 13%.

Clustering Methods for Determination of Optimal Locations of Container Storage and Distribution Centers

A mathematical model has been developed to determine the number and locations of container storage and distribution centers (CSDC) based on clustering methods, which allows mutually linking the various baseline parameters of production and the rail network with a variety of targets. A multi-criterion approach has been proposed to calculate the optimal variant of the CSDC network, taking into account the additional characteristics of the candidate railway stations, which allows, using vector optimization methods, practically determining the optimal places for the creation of the CSDC at known investment costs (the number of CSDC is set), as well as quantifying the optimal number of created CSDC (the number of CSDC is not set). Implementation of the proposed methodology allows us to move to scientifically sound decision-making in investment projects related to the development of transport and logistics infrastructure, improve the quality of transport and logistics services of cargo owners, organize a concerted delivery of goods to the terminal-logistics infrastructure, improve the use of rolling stock, reduce the cost of shipping goods in containers, thereby increasing the attractiveness of container transport.

ОЦЕНКА ЭФФЕКТИВНОСТИ РАСПРЕДЕЛИТЕЛЬНОГО ЦЕНТРА ПРИ РАЗНЫХ ВАРИАНТАХ КОНСОЛИДАЦИИ ГРУЗОПОТОКОВ

For the determination of a potential benefit from creation of a distribution centre the paper proposes a method and presents results of calculation of a decrease of total number of rides and total run of automobiles at various variants of goods consolidation. The authors have established a positive influence of the centre on intracity transportation. At the same time, high efficiency of the considered technology can be reached by involvement of a bigger number of consignees and by consolidation of a relatively small number of goods batches in one automobile at efficient routing and correct selection of location of a distribution centre.

Location of the city distribution center: scientific and methodological approach

Location of the city distribution center: scientific and methodological approach

Robust Optimization of the Multi-Objective Multi-Period Location-Routing Problem for Epidemic Logistics System With Uncertain Demand

The effective distribution of relief to an emergency logistics system plays a crucial role during the disaster response phase. Considering stochastic characteristics of relief demand, this study investigates the robust optimization of a multi-objective multi-period location-routing problem for epidemic logistics, a special emergency logistics, with uncertain scenarios. A corresponding robust multi-objective multi-period optimization model is proposed, which aims to determine the optimal location of temporary relief distribution centres and route planning simultaneously. The optimization objectives include the total travel time, the total cost, and the disutility of relief service. To solve the above optimization model, a preference-inspired co-evolutionary algorithm with Tchebycheff decomposition (PICEA-g-td) is given. The performance of the proposed PICEA-g-td is evaluated by comparing it with NSGA-II, MOEA/D and PICEA-g. The experimental results show that the proposed algorithm performs better than the other three algorithms in terms of the solution quality. Finally, some useful management insights are obtained.

Optimization of e-commerce distribution center location

Since the COVID-19 pandemic hit last year, countries locked their borders. Thus, international shipping deteriorates drastically. Simultaneously, social distancing increased the need for immediate online consumption and fast home delivery. In the non-digital world, products still need to be shipped to their destination using trucks, trains, airplanes, and ships. Simultaneously, requirements for volumes of goods, transport costs, external limiting factors, etc., must be precisely defined. The article aims to find the optimal location selection solution based on the created mathematical model of the Modified Steiner-Weber Problem with restrictive conditions. The model allows for the central warehouse's optimal location and minimizes distribution costs from the central warehouse to sub-warehouses/branches located in individual EU countries. The mathematical model has been applied to a case study of a selected e-commerce dealing, which has established branches in capital cities but does not have an established central warehouse. Systematization of literature sources and approaches to solving the problem of e-commerce distribution center location showed that 86% of the studied companies plan to use on-demand warehousing in the next three to five years. Therefore, the need for warehousing would be preserved. The authors noted that they do not necessarily need to have it in-house. Consequently, fulfillment centers and warehouses would likely continue to be a significant component in the future logistics system. This research would like to stress how important the management of the effective optimization of e-commerce distribution center location is and how to achieve it. The success of Amazon in the US, Europe, and Alibaba in China has genuinely redefined consumer expectations. With the emergence of services like Amazon Prime, consumers now expect same-day delivery. The solution enabling this evolution has been a mix of manufacturing where the production costs are optimal, just-in-time shipping, highly automated fulfillment centers, and mobile connectivity growth. The proposed model results showed that the best location for a central location and storage center concerning the e-commerce environment, including minimum annual transport costs, is near Bristol in the United Kingdom. Eighty-six percent of the companies in the study plan to use on-demand warehousing in the next three to five years, and the solution enabling this evolution has been a combination of manufacturing where the production costs are optimal, just-in-time shipping, highly automated fulfillment centers, and, to a growing extent, mobile connectivity.

Design of Distribution Centre Location for Small E-shop Consignments Using the Clark-Wright Method

The abstract deals with a design of a concept for parcel consignment deliveries to the end link of the supply chain City Hub. Utility vehicles are evaluated with the respect to the use of new technologies, the implementation of alternative fuels taking the environment into account. The designed concept was evaluated for the city of Olomouc from the economic efficiency point of view. The allocation of the logistic centre was performed using the problem of the column sum method. Location problems can be divided according to the shape of the objective function into covering problems, median location problems and centre location problems. According to the number of locating centres, the location problems can be divided into problems regarding single-facility locations and problems of multi-facility locations. Location problems are divided according to the character of location area into location problems in plane, discreet location problems or location on the transport network.

Reliable Fourth Party Logistics Location-Routing Problem Under the Risk of Disruptions

A smooth operation of the fourth party logistics supply chain network requires the cooperation of multiple distribution centers and third party logistics. Any unexpected disruption caused by a certain distribution center may lead to serious consequences to the whole fourth party logistics supply chain. Therefore, we study the reliable fourth party logistics location-routing problem in the network design considering disruption risk of distribution centers. In addition, to minimize the total cost of the proposed problem, a scenario-based integer programming model is established to locate distribution centers, to select proper third party logistic providers, and to accomplish the vehicle routing from distribution centers to customers. Then, a two-level heuristic framework is proposed to handle this NP-hard problem through dividing the original problem into two sub-problems. One is the reliable fourth party logistics location assignment problem, and the other is the fourth party logistics vehicle routing problem. These two sub-problems can be independently solved and iteratively composed to get to the solution of the original problem. Furthermore, numerical experiments are designed, and the effectiveness of the heuristic framework is tested by comparing the quality of solutions and running time with those calculated by using CPLEX. Managerial insights are also provided based on the calculation results.

Optimisation des Réseaux de Distribution des Produits Agroalimentaires: Modélisation et Application

A certain number of factors can affect the functioning of the distribution chains of large agrifood companies and impact their efficiency. Among them, poor adaptation to fluctuations in demand, imperfect control of production and transport costs and poor location of distribution centers. These dysfunctions can have negative consequences with high product prices, supply disruptions and customer dissatisfaction. The company is therefore required to review regularly the distribution plan for its products in order to optimize it: addition, deletion, relocation, reassignment of warehouses, delivery centers, etc. We propose, through a case study of the agro-food group Cevital (Algeria), a solution to the problem of restructuring supply and distribution networks, at a stage of development of this company. Using an operational research tool (mixed-integer linear programming), the study assesses four scenarios for structuring the company's distribution network and suggests, for decision-making purposes, strategic solutions for managers.

Research progress on logistics network optimization under low carbon constraints

In this paper, a literature review was conducted on the optimization of logistics network under low carbon constraints. This paper summarized the basic research process of logistics network optimization, and discussed the basic problems of logistics network optimization (distribution center location and vehicle distribution route optimization) and the compound optimization problems of logistics network (forward logistics network optimization and reverse logistics network optimization). In this paper, we mainly discuss the mathematical model constructed by one or more of the goals of minimum carbon emissions, minimum sum of total costs, minimum total delivery time and minimum total delivery distance, and the solving strategies using heuristic algorithms such as particle swarm optimization, genetic algorithm, and ant colony algorithm. It provided the latest technology in this field for the researchers of enterprise logistics network model and points out the future development trend.

Resilience Role of Distribution Centers amid COVID-19 Crisis in Tier-A Cities of India: A Green Field Analysis Experiment

Supply chain is the most critical lifeline of all business/non-business operations and processes in today’s world. The outbreak of the COVID-19 epidemic has a serious impact on organizations and society at large. Due to this pandemic spread, food supply chains are facing two unique unraveling emerging supply chain challenges: (a) supply shocks and (b) demand shocks. Stocking of consumer staples under such uncertain situations gives rise to uncertain peak demands of staple food, and hence striking bullwhip effect. The present study focuses on the staple food distribution among tier-A cities of India, namely Bangalore, Hyderabad, Chennai, Pune, Kolkata, Mumbai, and Ahmedabad. Using the software anyLogistix PLE edition, greenfield analysis was conducted to find the number of distribution centers required by these cities for food distribution and to reduce the transportation cost between the cities. Two key insights emerge from the analysis: (a) we need six potential areas to locate distribution centers (DCs)/ regional sites instead of a single DC; (b) transportation cost is reduced from US$21,327 to US$2,375. The major observation from the Green Field Analysis (GFA) reveals there is a need to reinforce and repair the operational efficiencies of DCs so as to reach the needy end consumers.

The Unified Power Quality Conditioner Control Method Based on the Equivalent Conductance Signals of the Compensated Load

This paper proposes a new control method for a Unified Power Quality Conditioner (UPQC). This method is based on the load equivalent conductance approach, originally proposed by Fryze. It can be useful not only for compensation for nonactive current and for improving voltage quality, but it also allows one to perform some unconventional functions. This control method can be performed by extending the orthodox notion of ‘static’ load equivalent conductance into a time-variable signal. It may be used to characterize energy changes in the whole UPQC-and-load circuitry. The UPQC can regulate energy flow between all sources and loads being under compensation. They may be located as well for UPQC’s AC-side as DC-side. System works properly even if they switch their activity to work either as loads or generators. The UPQC can operate also as a buffer, which can store/share the in-load generated energy amongst other loads, or it can transmit this energy to the source. Therefore, in addition to performing the UPQC’s conventional compensation tasks, it can also serve as a local energy distribution center.

Decision-making from multiple uncertain experts: case of distribution center location selection

The location selection of distribution center covers one of the important strategic decision issues for the logistics system managers. In view of the inherent uncertainty and inaccuracy of human decision-making, the future behavior of the market and companies, this paper adopts the improved multi-attribute and multi-Actor decision-making (MAADM) method as a fuzzy multi-attribute and multi-actor decision-making (FMAADM) method for solving the selection problem under an uncertain environment. The great strengths of our proposed method are: first, the integration of the decision-makers group preferences into the decision-making process, second, the consideration of the informations related to the alternatives and the criteria weights which are inaccurate, uncertain or incomplete, third, the verification of the obtained solution by both tests of concordance and non-discordance. To validate the FMAADM method, a decision support system was developed. Different experiments were provided based on comparative analysis of results and the sensitivity analysis. These experiments demonstrate the efficiency of our proposed method and its superiority over another existing methods.

Two-Phase Optimization Method for Determining Distribution Center Locations and Distribution Routes (Case Study: X Ltd.)

One of the main keys to establishing a company’s facilities is to determine the best location with consideration of proximity to customers. After determining the location using the P-Center method, the company aims to maximize its profit by minimizing the distribution costs. It can be minimized by finding the shortest route. The best route determination method used in this study is the Capacitated Vehicle Routing Problem. The initial solution was obtained from data processing with the Nearest Neighborhood algorithm. The routes obtained from this method are optimal local results so that they can still be optimized to obtain the optimal global results. The results will be reprocessed with improvement heuristics method, namely Simple Local Search to get the most optimal results. From this data processing, it will produce an output in the form of the location of the best facility and route construction by producing the minimum total of distribution cost.

Solving the problem of determining the optimal location of the logistics center, taking into account cost minimization

The problem of placing distribution centers for the delivery of goods as part of the optimization of product distribution is a strategic task that needs to be addressed. This article describes a model for determining the optimal location of a distribution center based on geographic coordinates. Based on the methodology of the model, it finds the most optimal location for a given demand. For a more accurate solution, the optimization algorithm does not include an abstract measurement system, but is designed to solve the problem of the location of the distribution center on a location map. An example is shown that the proposed model and algorithm are reliable and can effectively cope with solving problems of this kind. The model proposed in this article has not only a theoretical structure, but is also tested to solve practical problems of choosing the location of distribution centers.

Research on Location Selection of UAV Distribution Center Based on Improved Gravity Method

In order to speed up logistics distribution efficiency and reduce distribution costs, logistics companies around the world began to use drones for related distribution work. In addition to upgrading the hardware technology of UAV, optimizing the distribution path is also one of the ways to reduce the distribution cost of UAV distribution center. In this paper, the location of UAV distribution center will be studied theoretically based on the economic optimization and equipment maintenance optimization. Finally, the feasibility of the algorithm is verified by simple simulation application.