DPSO based on a min-max approach and clamping strategy for the evacuation vehicle assignment problem

The most challenging task during a flood event is to evacuate people from the affected areas to safer locations. The difficulty of this task is attributed to an uneven distribution of vehicles, a lack of timely assistance, a deficiency in decision making and poor coordination at the operational level. Although it is important to identify flood-prone areas, the assignment of vehicles to the appropriate evacuation routes is of primary importance. The latter consideration is a crucial determinant of the number of people who are saved in any emergency evacuation. This paper proposes an improved discrete particle swarm optimisation (DPSO) algorithm for solving the evacuation vehicle assignment problem (EVAP). Discrete particle positions are proposed that support the implementation of this DPSO. A min-max approach is used for the initial calculations of particle positions for the EVAP. This algorithm was computationally tested using different numbers of potentially flooded areas and compared with an average DPSO approach and with genetic algorithms. The findings of this study reveal that DPSO with a min-max approach that incorporates a new velocity clamping procedure offers good performance with respect to maximising the number of individuals who can be evacuated by vehicles from diverse locations for situations involving various numbers of potential flooded areas.