Distribution Center Location Research Articles

Including decision-makers preferences in the cost-deprivation trade-off during disaster interventions

PurposeIn this contribution, the purpose of this study is to extend the established social cost concept of humanitarian logistics into a preference-based bi-objective approach. The novel concept offers an efficient, robust and transparent way to consider the decision-maker’s preference. In principle, the proposed method applies to any multi-objective decision and is especially suitable for decisions with conflicting objectives and asymmetric impact.Design/methodology/approachThe authors bypass the shortcomings of the traditional approach by introducing a normalized weighted sum approach. Within this approach, logistics and deprivation costs are normalized with the help of Nadir and Utopia points. The weighting factor represents the preference of a decision-maker toward emphasizing the reduction of one cost component. The authors apply the approach to a case study for hypothetical water contamination in the city of Berlin, in which authorities select distribution center (DiC) locations to supply water to beneficiaries.FindingsThe results of the case study highlight that the decisions generated by the approach are more consistent with the decision-makers preferences while enabling higher efficiency gains. Furthermore, it is possible to identify robust solutions, i.e. DiCs opened in each scenario. These locations can be the focal point of interest during disaster preparedness. Moreover, the introduced approach increases the transparency of the decision by highlighting the cost-deprivation trade-off, together with the Pareto-front.Practical implicationsFor practical users, such as disaster control and civil protection authorities, this approach provides a transparent focus on the trade-off of their decision objectives. The case study highlights that it proves to be a powerful concept for multi-objective decisions in the domain of humanitarian logistics and for collaborative decision-making.Originality/valueTo the best of the knowledge, the present study is the first to include preferences in the cost-deprivation trade-off. Moreover, it highlights the promising option to use a weighted-sum approach to understand the decisions affected by this trade-off better and thereby, increase the transparency and quality of decision-making in disasters.

Bifuzzy-Bilevel Programming Model: Solution and Application

Bi-level programming is widely used in processing various questions, but it cannot deal with the complex and fuzzy information contained in problems. In order to solve such problems better with intricate and vague information that can be efficiently handled by bifuzzy theory, a bifuzzy–bilevel programming model that sets the parameters to bifuzzy variables is proposed in this paper, which can process complex realistic data more accurately and improve the feasibility and validity of bi-level programming models. To ensure the solvability of the model, the equivalent form of the bifuzzy–bilevel programming model is obtained by utilizing the expected value operator. According to the linear and nonlinear characteristics of the model, the Karush–Kuhn–Tucker condition and particle swarm optimization algorithm are employed to handle the problem, respectively. Finally, by taking the distribution center location problem of the supplier as an example, the bifuzzy–bilevel programming model is applied in practice to balance highly intricate customer demands and corporate cost minimization, obtaining the feasible solution of functions at the upper and lower levels, and the bifuzzy information in the problem can also be processed well, which proves the effectiveness of the proposed methodology.

A Customer Clustering Algorithm for Power Logistics Distribution Network Structure and Distribution Volume Constraints

Customer clustering technology for distribution process is widely used in location selection, distribution route optimization and vehicle scheduling optimization of power logistics distribution center. Aiming at the problem of customer clustering with unknown distribution center location, this paper proposes a clustering algorithm considering distribution network structure and distribution volume constraint, which makes up for the defect that the classical Euclidean distance does not consider the distribution road information. This paper proposes a logistics distribution customer clustering algorithm, which improves CLARANS algorithm to make the clustering results meet the constraints of customer distribution volume. By using the single vehicle load rate, the sufficient conditions for logistics distribution customer clustering to be solvable under the condition of considering the ubiquitous and constraints are given, which effectively solves the problem of logistics distribution customer clustering with sum constraints. The results state clearly that the clustering algorithm can effectively deal with large-scale spatial data sets, and the clustering process is not affected by isolated customers, The clustering results can be effectively applied to the distribution center location, distribution cost optimization, distribution route optimization and distribution area division of vehicle scheduling optimization.

Assessing the sustainability of using drone technology for last-mile delivery in a blood supply chain

PurposeDelivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user as fast as possible takes into account as one of the most important, expensive and, polluting segments in the entire supply chain. Regardless of economic challenges, the last-mile delivery faces social and environmental barriers to continuing operations while complying with environmental and social standards, therefore incorporating sustainability into last-mile logistic strategy is no longer an option but rather a necessity. Accordingly, the purpose of this paper is to consider a last-mile delivery in a blood supply chain in terms of using appropriate technologies such as drones to assess sustainability.Design/methodology/approachThe authors discuss the impact of drone technology on last-mile delivery and its importance in achieving sustainability. They focus on the effect of using drones on CO2 emission, costs and social benefits by proposing a multi-objective mathematical model to assess sustainability in the last-mile delivery. A preemptive fuzzy goal programming approach to solve the model and measure the achievement degree of sustainability is conducted by using a numerical example to show the capability and usefulness of the suggested model, solution approach and, impact of drone technology in achieving all three aspects of sustainability.FindingsThe findings illustrate the achievement degree of sustainability in the delivery of blood based on locating distribution centers and allocating drones. Moreover, a comparison between drones and conventional vehicles is carried out to show the preference of using drones in reaching sustainability. A sensitivity analysis on aspects of sustainability and specifications of drone technology is conducted for validating the obtained results and distinguishing the most dominant aspect and parameters in enhancing the achievement degree of sustainability.Originality/valueTo the best of the authors’ knowledge, no research has considered the assessment of sustainability in the last-mile delivery of blood supply chain with a focus on drone technology.

Efektifitas Transportasi dan Lokasi Terhadap Distribusi Logistik di Wilayah Komando Armada I TNI-AL

The delays and constraints that distribution centers have in supplying logistics that are often faced are related to transportation and transportation facilities that are not optimal, as well as the location of distribution centers to the remote Koarmada I area. In this study, an analysis of the effectiveness of the implementation of logistics distribution by a logistics distribution agency was carried out and the influence of the implementation of logistics distribution on supply performance to support the Koarmada I Marine Combat Operations. From the measurement model obtained using SEM-AMOS software on the three variables of Location, Transportation and Inventory that builds Logistic Distribution, Location variable has a high value of 0.566. This means that the effectiveness of the implementation of logistics distribution in distributing logistics supplies from the distribution center to Koarmada I is not effective. So that in order to answer the existing problems, the Indonesian Navy needs to plan the formation of a logistics supply distribution organization through organizational validation, building reserve locations that are in strategic positions, building infrastructure and managing logistics supplies in a comprehensive and integrated manner.

Application of FWA-Artificial Fish Swarm Algorithm in the Location of Low-Carbon Cold Chain Logistics Distribution Center in Beijing-Tianjin-Hebei Metropolitan Area

Green development is the hot spot of cold chain logistics today. Therefore, this paper converts carbon emission into carbon emission cost, comprehensively considers cargo damage, refrigeration, carbon emission, time window, and other factors, and establishes the optimization model of location of low-carbon cold chain logistics in the Beijing-Tianjin-Hebei metropolitan area. Aiming at the problems of the fish swarm algorithm, this paper makes full use of the fireworks algorithm and proposes an improved fish swarm algorithm on the basis of the fireworks algorithm. By introducing the explosion, Gaussian mutation, mapping and selection operations of the fireworks algorithm, the local search ability and diversity of artificial fish are enhanced. Finally, the modified algorithm is applied to optimize the model, and the results show that the location scheme of low-carbon cold chain logistics in Beijing-Tianjin-Hebei metropolitan area with the lowest total cost can be obtained by using fireworks-artificial fish swarm algorithm.

Bi-objective trapezoidal fuzzy mixed integer linear program-based distribution center location decision for large-scale emergencies

This paper aims at solving three important and challenging issues: (i) How to build a 0-1 mixed integer linear program-based distribution center location model for large-scale emergencies (we call emergency distribution center (EDC) location model for short). (ii) How to develop an effective method to convert the trapezoidal fuzzy EDC location model into a crisp one. (iii) How to demonstrate the validity, flexibility and superiorities of the constructed model and developed method. Considering the acceptance degree of fuzzy constraints to be violated, this paper defines a novel flexible ranking relation for trapezoidal fuzzy numbers (TrFNs) by using the α-cut set and analyzes its desirable properties. A bi-objective trapezoidal fuzzy EDC location model (BTFELM) is built for reflecting the urgency and uncertainty of large-scale emergencies. Some essential definitions and theorems are proposed for equivalently converting the fuzzy constraints of the BTFELM into crisp ones. By employing the graded mean integration representation of TrFN, the BTFELM is ultimately transformed into a single objective crisp EDC location linear program. Wenchuan earthquake case is studied to illustrate the practicality and validity of the proposed method. Furthermore, the sensitivity and comparative analyses are provided to justify the flexibility and superiorities of the proposed method. Finally, the accuracy analyses are conducted to illustrate the reliability of the proposed method.

Review on the optimization of medical supplies distribution under major public health emergencies

In recent years, frequent public health incidents have brought huge challenges to the economic development and emergency logistics systems of countries around the world. Facing the problems of unfair distribution of medical supplies and low distribution efficiency under major public health emergencies, this article systematically analyzes the literature on material distribution and distribution related to public health incidents in the past 20 years. The literature is reviewed from three aspects: the location and allocation of medical supplies distribution center, vehicle routing optimization, and location-routing optimization. Through the analysis of the existing research, several future research directions are proposed.

Distribution Center Location Model Based on Gauss-Kruger Projection and Gravity Method

The latitude and longitude coordinates are converted into Gaussian plane coordinates through the forward calculation of the Gauss-Kruger projection, and then the location is selected through the center of gravity method, and then the location result is converted into the latitude and longitude coordinates through the reverse calculation of the Gauss-Kruger projection. This method was then applied to the location of distribution centers among the four cities in Zhejiang Province, and reasonable results were obtained.

Incorporating sales and marketing considerations into a competitive multi-echelon distribution network design problem with pricing strategy in a stochastic environment

This paper presents a multi-echelon distribution network design problem with pricing strategy in a stochastic environment, where location, inventory, and pricing decisions in retail and wholesale channels are made simultaneously. The considered network is comprised of a central warehouse, a set of distribution centers, and a set of retailers and wholesalers. The objective of the problem is to maximize the supply chain profit. The decisions include the location of distribution centers and the allocation of retailers and wholesalers to them, order-size for each distribution center and product price at retail and wholesale channels for different payment conditions. A mixed-integer nonlinear mathematical model was formulated and solved using the Lagrangian relaxation method and a Genetic algorithm. Computational results indicate that Lagrangian relaxation algorithm has good performance in terms of objective function value and runtime, even in large sized problems.

Two-Objective Mathematical Model Considering Competitive Location, Distribution Scheduling and Priority Demand Points under Uncertainty

In the last two decades, competition between companies in the supply of goods and services has become a great reality for their development. Today, companies and factories need to integrate and flex all production activities from the supply of raw materials to the delivery of the final product to the consumer, in the process of supply and distribution of products. Distribution and support systems are part of the supply chain process, so that the efficient and efficient flow of storage of goods, services and related information is planned, implemented and controlled from the starting point to the point of consumption in order to meet customer needs. The problem of locating distribution centers focuses on how to select distribution centers from a potential set so that the relevant total costs are minimized. This study aims to minimize transportation costs in the supply chain by choosing the best way to deliver the product to the customer and location costs. In this model, a multi-objective function is used, which in the first objective seeks to maximize the profit from sales, and the second objective function seeks to minimize the distribution schedule.

Design of a CPFR, Location, Inventory and Routing Approach to Diabetes and High Blood Pressure Medicine Supply Network Planning

Objective: Designing a CPFR (collaborative planning forecasting and replenishment) model for the delivery of diabetes and arterial hypertension medicines from a health insurance company (EPS) to a healthcare provider (IPS) and comparing the performance of this collaborative chain to that of the traditional one through their corresponding supply chain costs. Methodology: A series of collaboration agreements involved in joint planning were established according to the designed CPFR model. This allowed (i) raising the levels of interaction between the health insurance company, the healthcare provider, the supplying pharmaceutical laboratories, and the patients; (ii) determining demand forecasts; (iii) locating distribution centers; and (iv) defining medicine distribution strategies oriented to the minimization of costs along the chain. Subsequently, the main differences between the current operation and CPFR models at the level of structure and decisions were characterized and then evaluated in terms of supply chain costs. Results: The significant impact of the proposed model is demonstrated. The total monthly cost of operating the chain is reduced by 11.2 % on average. Within the proposed innovation, an outstanding place is held by the savings reached in the purchase and distribution of medicines from the laboratory to the distribution centers, and by the customer satisfaction differences, which increased 15.3 % on average during the studied six-month period.

Determination Of Distribution Center Location In Xyz Small And Medium Enterprise (Sme) Using Center Of Gravity Method

XYZ Small Medium Enterprise (SME) is an SME that produces hijab. Research activities on XYZ aims to determine the operational cost of XYZ, caused by the far distance between the production site with retails. The analytical method which we use is by using the Center of Gravity. From the results of using the Center of Gravity method, the location of the new warehouse can be determined with the coordinates X = -7.51, Y = 110.45, which is located in Dusun II, Lencoh, Selo, Boyolali Regency, Central Java, XYZ can save distribution operational cost from IDR 22,711,150 to IDR 12,712,400. Therefore, XYZ can save distribution operational costs of IDR 9,998,750 or with a percentage of 55.97%. With the new distribution center location, it will shorten the distance from 1446 km to 264.6 km and reduce the transportation cost from the production site in Cicalengka, Bandung to the distribution center located in Dusun II, Lencoh, Selo, Boyolali Regency, Central Java.

Research on Ant Colony Algorithm for Location Planning of Distribution Center

The location of logistics center is affected by many factors. And it is an urgent problem to optimize the location selection and obtain the accurate location selection. Based on fully considering the actual distribution center planning problems, this paper introduces the problem of distribution center location planning model building and the steps of ant colony algorithm implementation. Then a large number of experimental simulations are used for instance verification to prove the rationality and effectiveness of the proposed ant colony algorithm to solve the distribution center allocation problem.

A Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm in Distribution Center Location Selection: A Case Study in Agricultural Supply Chain

Logistics is an important service sector, contributing to improving the competitiveness of the economy. Therefore, along with increasing the application of technology and effective business models, it is necessary to increase the connectivity of the infrastructure systems of industrial parks, roads, and seaports of regions and the country. Over the past decades, Vietnamese businesses have been step-by-step going through many stages from production, packaging, quality, hygiene, and safety to grasping new stages in the domestic and global value chain. In many industries, businesses are increasing the content of their own designs, exploiting brands, and approaching consumption networks in the target market. The role of the distribution center is becoming more and more important in ensuring a seamless and flawless supply chain. In particular, the distribution center is the most sensitive contact point between supply and demand in each enterprise. Therefore, the key mission of a distribution center is to reconcile supply and demand requirements. Distribution center location selection problems usually involve multiple quantitative and qualitative criteria that the decision maker must take into account for assessing the symmetrical impact of the criteria to reach the most accurate result. In this study, the authors propose a hybrid MCDM model based on Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm to support the distribution location selection problem of perishable agricultural products. The proposed model is then applied to the numerical case study of the sweet potato product of the Mekong Delta region of Vietnam to demonstrate the feasibility of the model. The contribution of this research is to propose an MCDM model for improving the efficiency of the agricultural supply chain through selecting a location distribution center. This proposed model can be applied to the agricultural supply chain around the world.

Research on Location Selection of Agricultural Products Logistics Distribution Center Based on Two-stage Combination Optimization Algorithm

The development of agricultural product logistics has a great impact on agricultural development. With the advancement of modern agriculture, agricultural product logistics is also facing important changes. On the basis of spatial analysis to determine the candidate address of the distribution center, this paper takes the lowest comprehensive cost as the objective function, establishes the distribution center location model, and solves it through the immune algorithm. On the basis of determining the distribution center, a distribution route optimization model with hard time windows for multiple distribution centers is established, and the tabu search method is used to solve the problem. According to the demand for time-sensitive fruit and vegetable agricultural products in a certain area and the actual circulation and distribution of fruit and vegetable agricultural products in newly developed enterprises, it is combined with the work done by the fruit and vegetable time-sensitive cold chain location planning model. Taking the grape distribution of Xinfadi Co., Ltd. in a certain area as an actual example of the model, using LINGO to solve and analyze the site selection model constructed in the paper, it verifies that the site selection plan for agricultural products that takes into account the characteristics of a complete cold chain and time-efficiency in this paper has a comprehensive low cost advantage.

Research on Location of Cold Chain Logistics Distribution Center with Low Carbon in Beijing-Tianjin-Hebei Area on the Basis of RNA-Artificial Fish Swarm Algorithm

In order to improve the existing problems of the artificial fish swarm algorithm, the fish swarm algorithm is improved by using the characteristics of RNA computing, and the RNA-artificial fish swarm algorithm is proposed. Since cold-chain food has the characteristics of perishable quality and can generate a large number of carbon emissions during its transportation, this paper establishes a model for optimizing cold chain low carbon logistics location in the Beijing-Tianjin-Hebei area, including factors such as food spoilage, refrigeration and carbon emissions. The logistics location optimization model is solved 30 times with the basic fish swarm algorithm and the RNA-artificial fish swarm algorithm respectively. The simulation results prove the effectiveness of the RNA-artificial fish swarm algorithm.

Multi-objective cold chain logistic distribution center location based on carbon emission.

The issues of food safety and environmental protection are attracting more and more attention. Everyday, a large number of cold chain products are delivered from suppliers to customers. The cold chain products require refrigeration equipment in delivery and should be delivered to customers as soon as possible. Therefore, the challenge of reducing carbon emission and improving the customer satisfaction should be solved. This study presents the impact of carbon emission, customer satisfaction, construction cost, and operation cost on the location of cold chain logistics distribution center. A multi-objective location model for cold chain logistics distribution center considering carbon emission is established. The carbon emission equivalent cost model considers the dynamic carbon emission during transportation and the static carbon emission of the distribution center. The penalty cost under the time window is introduced into the penalty cost model of customer satisfaction, which represents a multi-objective mixed-integer linear programming problem. A non-dominated sorting genetic algorithm II (NSGA-II) is used to design the program through double-layer composite coding. NSGA-II uses a fast non-dominated sorting approach to reduce the computational complexity of non-dominated sorting. This algorithm uses the elitist control strategy, which does not need to share parameters and is more efficient in the multi-objective optimization process. The numerical results show that the proposed algorithm can generate appropriate Pareto solutions for all objectives.

In-Depth Learning Layout and Path Optimization of Energy Service Urban Distribution Sites under e-Commerce Environment

This article uses a research method that combines theoretical research and empirical analysis. It first introduces the relevant theories of energy service city distribution sites in the context of e-commerce and then the types of energy service city distribution sites and the composition of energy service city distribution systems. The network layout of the service city distribution site and the location objectives, principles, and processes of the model is studied to determine the network layout plan of the energy service city distribution system in this paper. This paper fully considers the characteristics of the network operation mode of the energy service city distribution site and establishes an optimization model for the location selection and vehicle routing of the distribution center with the lowest total system cost under the simultaneous delivery service mode; based on the hierarchical solution strategy, a combination of deep learning is designed. Algorithms mainly include two-stage hybrid heuristic algorithm of cluster analysis, maximum coverage and genetic algorithm; simulation analysis is conducted to verify the effectiveness of the model and algorithm by data simulation, finally get the integrated optimization plan of distribution center location and routing, and put forward the operation strategy through the result expansion analysis. This paper studies the planning model based on the network layout planning of the energy service city distribution system under the e-commerce environment, aiming to promote the breakthrough development of urban smart logistics and prove the importance of the energy service city distribution station network layout planning. The purpose and results of the research are to reduce traffic and environmental pressures, achieve joint direct distribution, improve the efficiency of urban logistics and distribution, and solve the problem of the last mile of the city.

Green Supply Chain Network Optimization Under Random and Fuzzy Environment

This paper established a three-level supply chain composed of plants, distribution centers, and retailers, and studied the location of distribution centers in the supply chain network and the carbon emissions during processing and transportation. In a random and fuzzy environment, the research objective is to minimize the supply chain’s cost and carbon emission. The multi-objective uncertain equilibrium model of the green supply chain network is established by introducing opportunity constraints, and the stability of the model can be enhanced by using variance function and risk function. Then this research integrated the theory of stochastic programming and fuzzy mathematical programming and employed Monte Carlo simulation; the sample mean approximation, chance-constrained programming and fuzzy expectation to deal with the random parameters and fuzzy parameters in the model so that the uncertain model is clarified. Further, the authors used the hierarchical method, the weighted ideal point method, restriction method, and weighted ideal point method to solve the multi-objective model. Finally, a numerical example is provided to demonstrate the feasibility of the model.