ANALYSIS OF MODERN APPROACHES TO SOLVING DISCRETE AND CONTINUOUS MULTI-STAGE ALLOCATION PROBLEMS
DOI:
https://doi.org/10.32782/IT/2023-2-7Keywords:
multi-stage allocation problem, genetic algorithms, continuous allocation problems, optimal partitioning of sets.Abstract
The rapid development of logistics processes between regions and countries is the main reason for the complexity and elongation of material flow chains. The paper aims to consider various enterprise location models and their application in practice. The purpose of the paper is to review current problems and approaches to solving the issues of enterprise location, followed by an analysis of specific methods and identification of promising areas for further development. Various aspects of the multi-stage location problem are outlined, including the impact of geographic location, infrastructure, labor availability, demand and other factors on production efficiency. Various modeling techniques are investigated, including linear and nonlinear programming, genetic algorithms, hierarchy analysis and fuzzy logic. The publication discusses the impact of uncertainty and risks on the decision-making process of enterprise location. Particular attention is paid to analyzing the relationship between the location of enterprises and the reduction of negative environmental impact and sustainable development. The paper considers general mathematical formulations of practical problems that can be reduced to multistage location problems and proposes a classification of methods and approaches to solving problems of this type. Relevant scientific works for exact, heuristic, metaheuristic, multi-criteria, stochastic, integrated and continuum methods for solving a multi-stage location problem is reviewed. The pros and cons of each approach are mentioned. The authors also emphasize the problem of dimensionality that arises when solving problems in discrete statement when the number of objects to be placed is large. The limitations arising in various problems from the subject area were analyzed. The authors note that the existing solution approaches are effective. However, to consider the possible scaling of the problem, it is promising to study the combination of continuous methods with other solution approaches, such as metaheuristics or stochastic methods, further to improve their performance and practical scenarios applicability.
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