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

This paper presents a new multiple disinfection operation problem (MDOP) in 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 different from the typical vehicle routing problem since: (a) each building has to receive multiple spray applications of disinfectants; (b) the final spray application of disinfectant in each building is fixed; and (c) for safety, the time interval between two consecutive spray applications of disinfectants for each building must meet or exceed a specified minimum. The MDOP problem is NP-hard and difficult to solve directly. In this paper, we firstly develop an efficient encoding of spray operations to simultaneously determine the optimal sequence of buildings and their respective treatments with spray disinfectants. Secondly, we adopt immune algorithm to solve the presented MDOP. Finally, as a demonstration of our method, we solve the problem for a campus case 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 effectiveness of the adopted algorithm.