Modeling and Optimization of Generic Pull Supply Chain

Nowadays pull system is widely used in many industries. In the recent decade, many researchers adopt pull system to supply chain and present preference of this system. In this paper, a general Pull system for a stochastic supply chain process will be adapted along with optimizing a Pull Stochastic Supply chain. This Supply Chain, SC, is used with combining CONWIP and KANBAN, the two famous pull systems, for controlling the SC. Under assumptions of stochastic demand rate, stochastic production and transportation times, and stochastic distributions for backlog cost, a simulation modeling is used. In optimization process, concerning supply chain complexity, a simulation optimization procedure is applied along with a combination of simulation software package and methahuristic algorithms such as, genetic and Guided Local Search, GLS, algorithms, which are more flexible to solve the problem. Finally, the superiority of this design is observed.