Brute Force Algorithms for Job Shop Scheduling Problem

This paper discusses on how to find the scheduling of production processes which involve a number of jobs, processes and machines so that time needed to finished all jobs is minimal. It is carried out by finding the minimum processing time of all possible solutions schedule. This aims will improve the quality of a company's performance in producing more goods in a faster time. The method approach used is the Brute Force algorithm, where the algorithm was developed to calculate the make-span of all Job Shop Scheduling (JSS) problems provided using n x r x q data. The resulting data is generated in CSV format in simple text form. The algorithms was implemented using the Python programming language and run on an open source web tool. The results show that there is relationship between scheduling time and the number of jobs, processes and machines, and the complexity of program execution time is exponential to number of job being proceed. It is presented in the form of graphs.