Resource allocation in cloud manufacturing using bat algorithm

Abstract

Due to the advancements in information and communication technologies, growing volatility and business competitiveness, manufacturing industries have started to change their strategies of pursuing business. As a consequence of this change, cloud based manufacturing systems have emerged and one of the major challenges in such systems is optimal resource allocation to tasks in production line. However, utilising manufacturing cloud resources for satisfying job requirements needs much more effort. In our work, we present a better assignment of resource to tasks by having a qualitative analysis of match between task and the resources through the use of adaptive search mechanism. We propose a bat-based heuristic approach, to work on improving computation time, makespan and balance in workload. Progressive experimentation was made in casting of engine block and the results show that, usage of bat algorithm supports rapid convergence. Also, bat algorithm is used to provide optimal resource allocation among tasks. This algorithm improves workflow performance by minimising makespan. The proposed workflow approach satisfies large scale production requirements in manufacturing environment and can achieve optimal solution by minimising delays.