بهينه‌سازي سياست موجودي (R,Q) با رويكرد چندهدفه به‌كمك تكنيك بهينه‌سازي از طريق شبيه‌سازي (مطالعه ي موردي: شركت آريا گچ پلدختر)

Optimization of a Bi-Objective (R,Q) Inventory Policy Using Optimization Via a Simulation Technique. Case Study: Arya Chalk Industrial Company

در اين مقاله كاربرد شبيه‌سازي در بهينه‌سازي دو هدفه ي يك مسيله ي موجودي تحت سياست (R,Q) تشريح شده است. در اين سياست هرگاه سطح موجودي به R يا كم‌تر از آن برسد به اندازه ي Q سفارش صادر مي ‌شود. هدف اين تحقيق، تعيين مقادير نقطه ي سفارش مجدد و مقدار سفارش براي اين سياست در سيستم انبارداري شركت آريا‌گچ است، به‌طوري كه ضمن كاهش هزينه هاي نگه‌داري موجودي در انبارها، زمان انتظار مشتري در سيستم نيز كمينه ‌شود. بدين منظور سيستم انبارداري شركت كه متشكل از سه انبار است، با استفاده از يك مدل شبيه‌سازي در نرم افزار ED شبيه‌سازي شده است. پس از طراحي سناريوها و اجراي آنها در مدل شبيه‌سازي، مقادير ممكن براي دو متغير R و Q با كمك روش هاي سطح پاسخ و الگوريتم ژنتيك به دست آمده و نتايج با وضعيت فعلي شركت آريا‌گچ مقايسه شده است.

This paper describes the application of simulation in the bi-objective optimization of an inventory control problem, which is based on a (R,Q) policy, in an inventory storage system composed of three stores, for an industrial chalk production company. In this inventory policy, when the inventory level is R or less than R, the order is released in amounts of Q. This policy is placed in an inventory policy group with a fixed order size. In this system, customers enter with a probability distribution function and have a demand with a distinct probability distribution. Customers go to stores for their needs, and the system for accountability to customers replenishes the stores. In this paper, the objective is to determine the amounts of R and Q in order to minimize daily inventory holding costs in each store, and also to minimize customer waiting time in the system. For this purpose, using an optimization approach via simulation, the storage system of a company is simulated using an ED model. The simulation model indicates the structure, manner and operation of the system. In this model, using 4Dscript programming language, the manner of the system is coded. After model validation of the present condition of the system using Mann-Whitneys nonparametric test and through the 2k factorial design, scenarios were designed. By executing them in the simulation model, the amount of customer waiting time in the system and the mean of inventory holding costs in each store for (R,Q) compounds are obtained. Through the amount of objective function for each compound, non-linear regression models for inventory holding cost and customer waiting time in the system were obtained using Minitab. By solving the regression models using a genetic algorithm, possible answers for problem variables were obtained in a Pareto chart and the results were compared to the present condition of the system. In order to improve system operation among the compounds obtained from regression models, shown in the Pareto chart, the management specifies a mixture for determining the policy programming and inventory control of the company.