Rating Risk Factors Related to Dangerous Goods Transportation and Selecting an Ideal Warehouse Location

Considering the environment and human life, the importance of dangerous goods transportation should be carefully considered. Preventing damages during this transportation, anticipating the dangers, and minimizing the risks are vital components for businesses, human life, and the environment. Therefore, reducing/minimizing risks in dangerous goods transportation is a critical element of vital importance. This chapter is aimed to rate the risk factors related to dangerous goods transportation and select the most ideal warehouse locations due to the their importance for human and environmental health. There are a number of factors for that purpose. There are six provinces in the Eastern Black Sea region having the strategic function and structure. According to the decision makers' views and judgments, three provinces are determined in terms of dangerous goods transportation. Picture fuzzy sets-based AHP-TOPSIS methodology was used to analyze the problem of dangerous goods transportation and the most ideal warehouse location selection.

A Proposed Method to Evaluate Warehouse Location for 3PL Cold Chain Suppliers in Gulf Countries Using Neutrosophic Fuzzy EDAS

Logistics processes have been analyzed as one of the most critical expense items for companies. Companies that failed to manage their logistics processes well could not reach the desired growth rates, and some even disappeared. Logistics management without process optimizations can be time and money consuming for the companies. Logistics processes significantly influence organizations' efficiency. Logistic professionals should keep the process flow quality at a certain level, and some decision problems should be analyzed and answered well. Location selection of a warehouse is one of the most crucial decision problems of supply chain and logistics management. Alternatives are evaluated in quantitative and qualitative criteria to decide the best location alternative using scientific MCDM techniques. Different scientific methods have been developed and used to solve this problem. As for this study, the aim is to investigate the warehouse location selection of third-party cold chain logistics suppliers. The importance of keeping perishable products under the right conditions increased, since it is realized that cold chain warehousing and transportation prevent the product spoiled. Organizations can save their funds and time by having effective cold chain management. This study's main scope is to give a new scientific perspective for warehouse selection in cold chain logistics. MCDM technique of Interval-Valued Neutrosophic Fuzzy (IVNF) EDAS method has been used to evaluate essential criteria and choose the best option. Critical cities of Gulf Region countries have been considered alternatives in a numerical illustration.

Optimisation of the Two-Tier Distribution System in Omni-Channel Environment

This paper deals with the problem of the design and configuration of a distribution system that supports the delivery of goods to customers using various commercial channels. In this sense, a modelled distribution system, called an omni-channel distribution system, should ensure the delivery of the same products in different ways while guaranteeing its highest efficiency. The authors propose a single-criterion mixed-integer programming model for the configuration of a complex distribution system of goods in an omni-channel environment. A minimized cost function, composed of key logistics elements including transport, warehouse location, and manipulation processes, is the objective function. The model was experimentally verified, and as a result, potential savings of around 5–8% of the omni-channel design distribution system costs versus the multi-channel distribution system costs were identified. In the paper, an extended sensitivity analysis is also performed to show how specific parameters of the model can change the final recommendation.

A NEW INTEGRATED GREY MCDM MODEL: CASE OF WAREHOUSE LOCATION SELECTION

Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multi-criteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.

Applying the Maximum Entropy Model to Urban Freight Transportation Planning: An Exploratory Analysis of Warehouse Location in the Belo Horizonte Metropolitan Region

In Brazil, neglect and lack of data have complicated urban freight transportation planning. Belo Horizonte is one such example, where the administration’s disregard for urban freight transport has led to multiple negative externalities. Using the maximum entropy method, this study analyzed the influence of urban planning factors on warehouse location in the Belo Horizonte Metropolitan Region. Warehouse location was analyzed using 19 factors, with the results recorded on a map of logistic probabilities concerning locating warehouses. Given this is exploratory research, the model was validated by visual comparison to address the four hypotheses: (i) warehouses tend to be located near roads and railroads; (ii) warehouses tend to be located close to their consumer markets; (iii) warehouses tend to be located in urban areas; and (iv) warehouses tend to be located next to each other, creating clusters. These hypotheses were based on the extant literature and confirmed from observations of the Belo Horizonte Metropolitan Region. The results also demonstrated that the maximum entropy method can suitably model freight transportation in support of urban planning policy.

Study on Overseas Warehouse Location of Manufacturing Cross-border E-Commerce Enterprises Based on Multi-objective

As a new logistics mode, overseas warehouse can save transportation time for cross-border logistics and also solve the problem of customer return and exchange as soon as possible. This paper takesmanufacturing cross-border e-commerce enterprise logistics as the starting point, considering cost, market, environment, society and other factors, establishes a multi-objective overseas warehouse location model to set up alternatives, analyzes the location model by analytic hierarchy process, selects the optimal solution of overseas warehouse location in the alternatives, and verifies the method by an example. Finally, it puts forward targeted suggestions for manufacturingcross-border e-commerce enterprises to establish overseas warehouses, and then promotes the new logistics mode of manufacturingcross-border e-commerce overseas warehouses to mature and standardize.

Designing a Multi-Stage Transport System Serving e-Commerce Activity

In this paper, the author designs an e-commerce transport system, which covers the locations of producers’ facilities, distribution warehouses, and the business customers and deliveries among them. The study aims to identify the best locations for warehouses to increase efficiency in multi-stage transport systems. To reach this goal, the author revises distance metrics and suggests a methodological framework useful for warehouse location selection and practical applications. The empirical research is delivered by selecting a warehouse location using the maximal coverage model and mandatory closeness distance condition. After analyzing four warehouses’ alternatives, results are presented by applying various distance metrics. The results show that the selection of the location of the main warehouse depends on the level of returns that are defined by using the Mersenne Twister algorithm, and the distance calculation metrics representing differences in ranking. By the end of the study, the recommendation is given to apply the presented methodological approach for decision-makers seeking to improve service distances where decisions are made using path-based service distance criteria. The increase of efficiency is important from a policy development perspective, as findings of the study could help to reduce transport delivery costs for customers.

Solving the Multi-Commodity Single-Stage Capacitated Warehouse Location Problem Using Bat Algorithm

The warehouse location problem is so important in supply chains management. In concerns with optimize the assignment of warehouses in order to minimize the total costs related to transportation and service costs. In this paper, a mathematical model for the multi-commodity single-stage capacitated warehouse location problem is presented. A bat algorithm is developed for solving the problem and an illustrative example is presented to show its implementation. The computational results is done on a large sized problem to show the efficiency of the proposed algorithm.