Scalable and energy-efficient task allocation in industry 4.0: Leveraging distributed auction and IBPSO

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0314347 - e0314347

Published: Jan. 16, 2025

Industry 4.0 has transformed manufacturing with the integration of cutting-edge technology, posing crucial issues in efficient task assignment to multi-tasking robots within smart factories. The paper outlines a unique method decentralizing auctions handle basic tasks. It also introduces an improved variant Binary Particle Swarm Optimization (IBPSO) algorithm manage complicated tasks that require multi-robot collaboration. main contributions we make are: design auction decentralization (AOCTA) which allows for and flexible distribution dynamic contexts, optimization coalition formation complex jobs by using IBPSO improves efficiency energy decreases cost computation as well thorough simulations show our proposed significantly surpasses conventional methods efficiency, completion rates terms usage, rate, scaling system. This research contributes development through providing effective solution aligns sustainability objectives addresses operational environmental impacts. Addressing challenges posed allocation distributed systems, these advanced technologies provide comprehensive solution, facilitating evolution innovative systems.

Language: Английский

An automated negotiation model based on agents’ attribute preference with emotional deception

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127448 - 127448

Published: March 1, 2025

Language: Английский