An emergency response system by dynamic simulation and enhanced particle swarm optimization and application for a marine oil spill accident

An emergency response system is important to protect the public and the environment and mitigate the negative effects from major accidents or natural disasters. It helps minimize time and losses by optimizing response operations and use of resources. Marine oil spills, as a typical accident, can cause significant, long-term and adverse impacts on ecological, social and economic systems. An efficient response system can significantly reduce both overall response time and cost especially when dealing with a large-scale spill. This paper proposed an emergency response system based on dynamic process simulation and system optimization modeling. This was achieved by the development of an enhanced particle swarm optimization (ME-PSO) algorithm with outstanding convergence performance and low computation cost characteristics which integrated multi-agent theory and evolutionary population dynamics. The performance was evaluated using various PSO algorithms with 13 benchmark functions under 48 parameter combinations. A case study on a representative marine oil spill was conducted to demonstrate the proposed methodology and its value in supporting emergency response decision-making. Allocation and deployment of responses from multiple response centers were optimized to save time and increase recovery efficiency with the process simulations of resource dispatch, oil weathering and oil removal. The research not only contributed to emergency decision making through an integrated, dynamic and simulation-optimization coupling approach but also provided emergency responders a powerful tool to improve their response capabilities in dealing with emergencies such as marine oil spills.