Strategic Warehouse Location Selection in Business Logistics: A Novel Approach Using IMF SWARA–MARCOS—A Case Study of a Serbian Logistics Service Provider

Abstract

Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business logistics, exerting a direct influence on the efficiency and cost-effectiveness of supply chain operations. In the realm of business logistics, decisions regarding the location of facilities, including warehouses, distribution centers, and manufacturing plants, assume a pivotal role in shaping the overarching logistics strategy. Warehouses, serving as pivotal nodes in the supply chain network, establish crucial links at both local and global markets. They serve as the nexus connecting suppliers and customers across the entire supply chain, thus constituting indispensable elements that significantly impact the overall performance of the supply chain. The optimal location of warehouses is paramount for efficient supply chains, ensuring minimized costs and bigger profits. The decision on warehouse location exerts a profound influence on investment costs, operational expenses, and the distribution strategy of a company, thereby playing a substantial role in elevating customer service levels. Hence, the primary objective of this paper is to propose a novel methodology grounded in the application of the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA)-Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods for determining warehouse locations tailored to a logistics service provider (LSP) operating in the Serbian market. Through the definition of seven evaluation criteria based on a comprehensive literature review and expert insights, this study aims to assess five potential locations. The findings suggest that the proposed model offers great decision support for effectively addressing challenges akin to the one presented in this study.

Designing a Sustainable Nonlinear Model Considering a Piecewise Function for Solving the Risk of Hazardous Material Routing-Locating Problem

“…The two constants A and B also consider the effects related to the type of hazardous substance. Equation (2) states that the inventory of the factory in each period is equal to the inventory of the previous period plus the amount of production in that period minus the amount of goods to customers. Equations ( 3) and (4) determine warehouses' maximum and minimum capacity limits, respectively.…”

“…Finding the best locations for logistics facilities can minimize the overall transportation risk and cost. It is important to determine the most secure routes for travel between the starting point and the destination while accounting for variables like traffic volume, sensitivity to environmental changes, and roadways [2], creating a bi-level objective function that finds the best transportation routes after first optimizing distribution center locations [3]. Considering the decision-maker's preferences on risk mitigation, such as putting first risk reduction over cost minimization.…”