A genetic algorithm approach for modelling and optimisation of MAJSP- Part I: Modelling

This paper and its companion (Part 2) will focus on Multi-Attributes Job-Shop Scheduling Problem (MAJSP). MAJSP is an extension of classical JSP. It represents more realistic scheduling problems since it includes more constraints of jobs. The objectives for part 1 are first to investigate whether the provided resources are appropriate for one month schedule and second to maximise the profit for a MAJSP by different methods of resource allocations. In the second part, the effect of genetic operators on the optimal solution obtained by the previous part will be discussed. In a MAJSP, more attributes introduce more types of resources. The resources are in terms of labour, material, and capital which can be restricted to be equally or non-equally allocated to the machines. Here, two algorithms were developed based on these assumptions and it was found the latter approach yields better results in terms of optimality and convergence speed.