scholarly journals Simulation optimization of an inventory control model for a reverse logistics system

2022 ◽  
Vol 11 (1) ◽  
pp. 43-54 ◽  
Author(s):  
Hanane Rachih ◽  
Fatima Zahra Mhada ◽  
Raddouane Chiheb
Keyword(s):  
Inventory Control ◽  
Reverse Logistics ◽  
New Products ◽  
Discrete Event ◽  
Control Policy ◽  
Control Model ◽  
Logistics System ◽  
Event Simulation ◽  
Inventory Control Policy ◽  
Inventory Control Model

Nowadays, companies are recognizing their primordial roles and responsibilities towards the protection of the environment and save the natural resources. They are focusing on some contemporary activities such as Reverse Logistics which is economically and environmentally viable. However, the integration of such an initiative needs flows restructuring and supply chain management in order to increase sustainability and maximize profits. Under this background, this paper addresses an inventory control model for a reverse logistics system that deals with two separated types of demand, for new products and remanufactured products, with different selling prices. The model consists of a single shared machine between production and remanufacturing operations, while the machine is subject to random failures and repairs. Three stock points respectively for returns, new products and remanufactured products are investigated. Meanwhile, in this paper, a modeling of the problem with Discrete-Event simulation using Arena® was conducted. Regarding the purpose of finding, a near-optimal inventory control policy that minimizes the total cost, an optimization of the model based on Tabu Search and Genetic Algorithms was established. Computational examples and sensitivity analysis were performed in order to compare the results and the robustness of each proposed algorithm. Then the results of the two methods were compared with those of OptQuest® optimization tool.

scholarly journals Simulation of a stochastic multi-echelon distribution supply chain under a continuous inventory control policy

2020 ◽  
Vol 9 (2) ◽  
pp. 262
Author(s):  
Hamid Ech-cheikh ◽  
Abdessamad Douraid ◽  
Khalid El Had
Keyword(s):  
Distribution System ◽  
Initial Conditions ◽  
Discrete Event ◽  
Control Policy ◽  
Simulation Framework ◽  
Event Simulation ◽  
Proposed Model ◽  
Inventory Control Policy ◽  
Distribution Process ◽  
Key Variables

Multi Echelon Distribution System (MEDS) is a multifaceted system focusing on integration of all factors involved in the entire distribution process of finished goods to customers. This paper proposes a simulation framework at the operational level of MEDS. The proposed model includes three echelons, based on discrete-event simulation approach, where the performed operations within our system are depending on several key variables that often seem to have strong interrelationships. It is necessary to simulate such complicated system, in order to understand the whole mechanism, to analyze the interactions between various components and eventually to provide information without decomposing the system. The simulation framework is used to evaluate the performance of the considered system at initial conditions and to compare it with different scenarios generated by simulation running. The study concludes with an analysis of system performance and the finding results according to each scenario.   

scholarly journals Simulation-Optimisation Approach to Stochastic Inventory Control with Perishability

2019 ◽  
Vol 22 ◽  
pp. 9-14
Author(s):  
Ilya Jackson
Keyword(s):  
Inventory Control ◽  
Discrete Event ◽  
Control Policy ◽  
Control Parameters ◽  
Stochastic Inventory ◽  
Event Simulation ◽  
Multiple Products ◽  
Stochastic Inventory Control ◽  
Simulation Optimisation ◽  
Total Inventory

In order to tailor inventory control to urgent needs of grocery retail, the discrete-event simulation model with realistic perishability mechanics is proposed in the paper. The model is stochastic and operates with multiple products under constrained total inventory capacity. Besides, the model under consideration is distinguished by quantity discount, uncertain replenishment lags and lost sales. The paper presents both mathematical description and algorithmic implementation. An optimisation framework based on a genetic algorithm is also proposed for deriving an optimal control policy. The proposed approach contributes to the field of industrial engineering by providing a simple and flexible way to compute nearly-optimal inventory control parameters.

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