Rescheduling of job – shop using genetic algorithm – a case study

Scheduling concerns the allocation of limited resources overtime to perform tasks to fulfill certain criterion. One of the most popular models in scheduling theory is that of the job-shop scheduling, as it has earned a reputation for being notoriously difficult to solve. A job-shop scheduling problem comes under the category of combinatorial optimization problems and is very difficult to solve by conventional optimization techniques. Many scheduling problems from manufacturing industries are complex in nature and are to be best known about the difficult combinatorial optimization problems with a finite number of feasible solutions. A machine shop with four numbers of machines and five numbers of jobs and the following assumptions are taken into account and the machines are available at zero time and there are no breakdowns, machine processes one operation at a time and once an operation initiates processing on a given machine the machine stops only when the operation is over and the processing times are deterministic. In this present work, a rescheduling is done for the existing job-shop in a small scale industry and this problem is solved using the non-traditional optimization technique like Genetic Algorithms. Their performances are depicted graphically to exhibit how they have converged to the optimal solution.