Immune-based evolutionary algorithm for determining the optimal sequence of multiple disinfection operations

This paper presents a new Multiple Disinfection Operation Problem (MDOP) according to which several buildings have to be sprayed with various disinfectants. The MDOP seeks to minimize the total cost of disinfection operations for all buildings. The problem is dierent from the typical vehicle routing problem since (a) each building has to receive multiple spray applications of disinfectants; (b) the nal spray application of disinfectant in each building is xed; (c) for safety, the time interval between two consecutive spray applications of disinfectants for each building must meet or exceed a specied minimum. The MDOP problem is NP-hard and dicult to solve directly. In this paper, rst, an ecient encoding of spray operations is developed to simultaneously determine the optimal sequence of buildings and their respective treatments with spray disinfectants. Second, immune algorithm is adopted to solve the presented MDOP. Finally, as a demonstration of our method, the problem for a campus case is solved to determine the optimal disinfection strategy and routes, assuming both single and multiple vehicle scenarios. Numerical results of immune algorithm are discussed and compared with those of genetic algorithm and PSO to show the eectiveness of the adopted algorithm.