Intellectualization of Lean Production Logistic Technology Based on Fuzzy Expert System and Multi-agent Metaheuristics

Abstract

The paper discusses the intellectualization of lean production in order to minimize the costs main groups that do not develop customer value for the end user in supply chain management industrial enterprises by creating optimization methods based on multi-agent metaheuristics and an adaptive fuzzy expert system for evaluating equipment load efficiency, the use of which is aimed at creating “perfect,” and, consequently, competitive supply chains for economy globalization and intellectualization. The possibility of minimizing costs associated with unnecessary (unjustified) movements of goods and personnel has been substantiated, and it is also proposed to minimize losses associated with expectations, with managing stocks and determining the shortest path of movement of goods through multi-agent metaheuristic methods based on particle swarm optimization and simulated annealing. The proposed methods provide control over the convergence rate of the method, providing global (at initial iterations) and local (at final iterations) searches by simulating annealing, the possibility of discrete and conditional optimization through the random key technique and the penalty function. An adaptive fuzzy expert system for assessing the efficiency of equipment load has been developed which simplifies the interaction between the operator and the computer system through the use of quality indicators and also allows the identification of its parameters using the proposed multi-agent metaheuristics. The proposed optimization methods based on multi-agent metaheuristics and an adaptive fuzzy expert system allow intellectualizing Lean Production logistic technology for industrial enterprises. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.