Autors: Lazarova, M. K., Nikolov, D. A.
Title: Metaheuristics and Machine Learning for Resource Planning Optimization
Keywords: enterprise resource planning, optimization, job shop scheduling, metaheuristics, machine learning

Abstract: The paper outlines the enterprise resource planning and business process management as an optimization problem and describes several metaheuristics and machine learning algorithms that are proven to effectively and efficiently solve the job shop scheduling problem. A workflow of an optimization module for resource planning is suggested that uses metaheuristics and machine learning algorithms for solving the optimization problem for enterprise resource planning. Based on the workflow of the proposed optimization module a multiagent system for resource planning and business process management is developed that allows integration of the resource planning module to MOM and/or ERP for flexible and adaptive resource management in a multi-agent system environment.

References

    Issue

    Journal “Computer and Communications Engineering”, vol. 13, issue 1, pp. 26-35, 2019, Bulgaria, ТУ-София, ISBN ISSN 1314-2291

    Вид: статия в списание, публикация в реферирано издание