Optimization in science and engineering
zohre kiapasha; ali salmasnia
Abstract
Purpose: Cloud manufacturing is a service-oriented production model that centralizes production resources available in different geographical locations to respond to specific customer needs. One of the main issues in cloud manufacturing systems is the proper allocation of sub-tasks to enterprises and ...
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Purpose: Cloud manufacturing is a service-oriented production model that centralizes production resources available in different geographical locations to respond to specific customer needs. One of the main issues in cloud manufacturing systems is the proper allocation of sub-tasks to enterprises and their optimal scheduling. Most studies in the literature assume that all tasks have only one type of structure, although it is possible to have tasks with different structures in one order set. Furthermore, existing scheduling models in the cloud manufacturing literature tend to assume that all tasks are available at time zero and that the logistics time/cost among enterprises is negligible. Therefore, in this study, an optimization model with three objective functions of task completion time, the cost imposed on the cloud manufacturing system, and the quality of the selected services is developed in which to get closer to the real world, three features are included in it: 1) the possibility of tasks with two structures, series and parallel, 2) different arrival times of tasks in the cloud manufacturing system, and 3) time/cost of logistics between different enterprises.
Methodology: First, six examples with different numbers of tasks and subtasks are designed with both sequential and parallel structures. In order to accurately solve the proposed model and achieve the global optimum, the CPLEX solver is used in the GAMS software.
Findings: In order to verify the importance of the characteristics of the developed model, two comparative studies are carried out. In the first comparative study, the presented model is compared with a similar model in which it is assumed that all tasks are available at time zero. The second comparative study examines the effect of considering logistics time/costs between enterprises when allocating subtasks to services. The results of the comparative studies show the misleading level of the cloud manufacturing manager in the face of the reduced models.
Originality/Value: The output of this research is to present a model for the simultaneous scheduling of tasks with sequential and parallel structures, taking into account the different task arrival times and logistics in the cloud manufacturing system.