Optimal production rate in production planning problem with simulation optimisation approach by simulated annealing

Abstract

In manufacturing environments, the production planning is at the high level of production and operation management. This paper intends to plan a flow shop manufacturing system producing multi products during multi periods. By planning, the optimal production rate of each product in every period will be determined. In order to specify the optimal production rate, three objectives must be met simultaneously. Planning is done in a stochastic situation and some uncertain parameters are considered for the problem. The simulation-optimisation approach was used and SA algorithm was chosen as the optimiser. Ultimately, after generating 225 new feasible solutions, the optimal production rate was determined. Results showed the trend of searching new solutions reached to a convergence and the average value of objective function decreased from 222,657 to 56,430 and it has been a remarkable reduction. So, the simulation optimisation approach is capable in solving uncertain production planning model even by considering multi objectives simultaneously.

Maintenance, repair, and operations inventory reduction and operational development

“…Industrial systems have become more complex, which makes service and spare part availability more critical. Maintenance has significance for the optimal production rate -merely considering machines while uptime and downtime are stochastic can be problematic (Sajadi and Rad, 2016). The lack of spare parts may lead to significant production losses without compensation.…”

Optimization of an economic production quantity-based system with random scrap and adjustable production rate

“…Numerical examples were provided to demonstrate their model and results. Additional studies related to different aspects of fabrication systems with variable or adjustable production rates can also be found elsewhere [19][20][21][22][23][24][25][26][27]. In summary, with the aim of addressing aforementioned scrap and capacity increase issues, and providing production managers with a decision support-typed of system to deal with these practical situations, this study develops an exact model to portray the EPQ-based replenishment system with random scrap and adjustable production rate, and explores their effects on the optimal operating decisions.…”