Multi-agent method of constructing daily-shift schedule for real-time industrial resource management
Abstract
Introduction: Coordinated production resource management of enterprises manufacturing electrical products is a complex problem with a high level of complexity due to the variety of types of resources used, and the dependence of production processes on a variety of factors and conditions. The traditional scheduling methods are not efficient enough for this problem. Purpose: Developing a method for rapid scheduling of electrical equipment production, based on the multi-agent approach. Results: A multi-agent method is developed for constructing daily-shift schedule for managing production resources of an enterprise manufacturing electrical products, based on the subject area ontology, given criteria, preferences and limitations. The orders consist of related operations described by technological cards. In the iterative messaging process, the scheduler agents improve the current values of load uniformity criteria and minimize the execution time for building daily-shift jobs. The developed method of managing the production resources allows you to build schedules for performing related operations in a system of resources by real-time events. When executing an order pool at LLC «PC» Electrum» (Samara city), the uniformity of equipment load and performers was well maintained, and the number of delays in fulfilling the orders was reduced by 10 %. Practical relevance: The system developed based on the proposed method can work either autonomously or along with an existing system of warehouse accounting of materials and finished products. The approach is not limited to the described subject area, being applicable in other industries which require similar production tasks. The economic effect is expected to be obtained by reducing idle production resources and improving their efficiency.Published
2018-10-19
How to Cite
Lada, A., & Mayorov, I. (2018). Multi-agent method of constructing daily-shift schedule for real-time industrial resource management. Information and Control Systems, (5), 112-119. https://doi.org/10.31799/1684-8853-2018-5-112-119
Issue
Section
Control in social and economic systems