Agent-based simulation system for optimising resource allocation in production process

Abstract

Efficient sequencing of processes and resource allocation are critical in production planning scenarios, such as manufacturing workshops and construction projects, to enhance efficiency and reduce operational costs. Resource allocation in such environments is often challenged by temporal constraints, process interdependencies, and resource limitations, which complicate scheduling and increase the risk of delays. This study presents a multi-agent-based simulation system to address these challenges. A scheduling optimisation model is developed to simulate and optimise resource allocation in complex processes with network structures and temporal constraints. The primary objective is to minimise production completion time while ensuring effective resource allocation. Additionally, an adaptive, partially distributed Agent-Based Modelling and Simulation framework is proposed to simulate the execution logic of real-world processes, integrating key factors such as resource limitations, process interdependencies, and real-time decision-making. A priority-based genetic algorithm is also designed and embedded into the multi-agent system to further optimise process sequencing and resource distribution. Simulation experiments across varying case scales validate the model and algorithm. This study highlights the potential of agent-based simulation for solving complex engineering challenges and provides new insights for addressing resource allocation problems in network-structured, time-constrained environments.