An autonomous decentralized scheduling algorithm for a job shop process with a multi-function machine in parallel

Deals with a job shop scheduling problem with a multi-function machine. In this problem, the multi-function machine can process all operations, and each operation is processed by either a single-function machine or the multi-function machine. This problem has two objective functions. One is to minimize the sum of the tardiness of each job, and the other is to maximize the working time of the multi-function machine because of the operating cost of the machines. An autonomous decentralized scheduling algorithm is proposed to obtain a compromise solution of this problem. In this algorithm, a number of decision makers are called subsystems, which cooperate with one another in order to attain the goal of the overall system. In our algorithm, all jobs and the multi-function machine are defined as subsystems because their objective functions are competitive. They determine the scheduling plan on the basis of their cooperation and their own objective functions. The effectiveness of the algorithm is investigated by examining numerical results