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Emergency resources dynamic assignment using a repast symphony-based simulation
This paper addresses stochastic dynamic assignment of perishable goods in a scale-free network. We develop an agent-based simulation model in which the supplies and demands for a single perishable commodity are generated at each node (agent) in the network. We match supplies and demands with several pre-specified assignment rules and given various commodity decay durations. A utility is associated with each assignment based on the spatial proximity between the supplier and the recipient. We assess various rules in terms of overall network utility. Our computational results show that 1) it is beneficial to use hybrid assignment rules that integrate the spirit of system-wide assignment and that of local preferred assignment; 2) it may be beneficial to allow agent behavior changes with certain degree of autonomy.
Emergency resources dynamic assignment using a repast symphony-based simulation
This paper addresses stochastic dynamic assignment of perishable goods in a scale-free network. We develop an agent-based simulation model in which the supplies and demands for a single perishable commodity are generated at each node (agent) in the network. We match supplies and demands with several pre-specified assignment rules and given various commodity decay durations. A utility is associated with each assignment based on the spatial proximity between the supplier and the recipient. We assess various rules in terms of overall network utility. Our computational results show that 1) it is beneficial to use hybrid assignment rules that integrate the spirit of system-wide assignment and that of local preferred assignment; 2) it may be beneficial to allow agent behavior changes with certain degree of autonomy.
Emergency resources dynamic assignment using a repast symphony-based simulation
Liu Hongwei, (author) / Huang Yanbo, (author) / Yao Dongliang, (author) / Zhen Jianfhu, (author)
2010-01-01
444528 byte
Conference paper
Electronic Resource
English
Springer Verlag | 2021
|DataCite | 1906
|Springer Verlag | 2021
|Springer Verlag | 2021
|