A hybrid cuckoo search algorithm in parallel batch processing machines with unequal job ready times

This paper deals with the problem of scheduling identical parallel batch processing machines. In this scheduling system, each machine processes a set of jobs in a batch simultaneously and each job in the batch is characterized by its processing time, ready time and job size. We propose a hybrid discrete cuckoo search (HDCS) algorithm to minimize makespan for this scheduling problem. The HDCS is constructed, based on a modified variable neighborhood search and cuckoo search algorithm. In the proposed algorithm, we present a modified Lévy flight in the cuckoo search to transform a continuous position in the HDCS into a discrete schedule for generating a new solution. The process parameters of the proposed HDCS are tuned by implementing the desirability-based Taguchi method to optimize both solution quality and run time. The results of exhaustive computational experimentation on a large number of randomly generated sparse as well as non-sparse problem instances show that the proposed algorithm is more effective and efficient than the state-of-the-art algorithms.