Business process optimization using the ant colony system

Process optimization is a key consideration in workflow management. Implementing an efficient workflow may improve customer satisfaction and enhance productivity of an enterprise. Many optimization tools have been introduced to solve scheduling problems in the manufacturing environment, but most of them have not drawn much attention of decision makers for workflow analyses. This is mainly due to the difference between business operations and manufacturing processes that the process optimization tools cannot be directly applied for analyzing business workflows. Scholars have associated the attributes of workflow in the business environment with those of scheduling concepts to facilitate the use of job shop scheduling techniques for solving workflow problems. However, there is still not much discussion on the use of metaheuristic algorithms for workflow analyses. This paper proposes the use of a systematic approach that entails the ant colony optimization algorithm for identifying the best task sequence in support of processing time analyses. The applicability of the proposed approach is demonstrated with a case example. The result shows that a better operation sequence in terms of shorter processing duration can be obtained by the proposed approach.