چکیده:
این مطالعه با هدف بررسی تأثیر افزایش قیمت شناخته شده بر مدل موجودی دارای توزیع یکنواخت و نمایی برای فاصله بازپرسازی انجام شده است. این مقاله بهینه سازی تصمیمات کنترل موجودی را برای محصولات فاسد شدنی با در نظر گرفتن افزایش قیمت شناخته شده، فاصله احتمالی بازپرسازی، محدودیت ظرفیت انبار و سفارش مجدد بررسی می کند. برای به دست آوردن مقدار سفارش موجودی ، مسئله به گونه ای مدل می شود که تابع صرفه جویی در هزینه کل از تفاوت بین خط مشی سفارش بهینه برای سفارش های خاص و معمولی به دست می آید. دو وضعیت مورد بحث در این مطالعه به شرح زیر است: (1) مدل سازی مسئله بدون محدودیت. و (2) در نظر گرفتن محدودیت برای ظرفیت انبار. برخی آزمایشهای محاسباتی برای بررسی تأثیر پارامترهای مختلف بر عملکرد صرفهجویی در هزینه انجام میشوند. در این مطالعه برای مسئله محدودیت، از الگوریتم ژنتیک (GA) و بهینهسازی ازدحام ذرات (PSO) استفاده شده است. عملکرد GA و PSO از نظر مقادیر صرفه جویی در هزینه و زمان محاسبه مقایسه شده است.بر اساس نتایج این مطالعه، الگوریتم GA عملکرد بهتری نسبت به PSO دارد. بر این اساس، برای یک مساله نامحدود، با استفاده از مشتق تابع سود و انجام تحلیل حساسیت، تأثیر برخی از پارامترها مانند تقاضا، قیمت فروش، هزینه نگهداری پس از افزایش قیمت، λ در توزیع نمایی، طول دورهها در توزیع یکنواخت، نرخ فاسد شدن بر روی متغیر تصمیم، مقدار سفارش و سود به دست آمده است.
Purpose: This study aims to investigate the influence of known price increases on the inventory model regarding both uniform and an exponential distribution of replenishment intervals with the partial backorder. It examines the optimization of inventory control decisions for deteriorating products considering a known price increase, probabilistic replenishment interval, warehouse capacity constraint, and partial back-ordering.Design/methodology/approach: To obtain the specific inventory order quantity, the problem has been modeled in such a way that the total cost savings function is obtained from the differences in the optimal order policy for both special and regular orders. The two situations discussed in this study are: i) unconstrained problem modeling, and ii) constrained problem. Some computational experiments have been performed to examine the effects of various parameters on cost savings performance. For the constrained problem, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been used and their results have been compared in terms of the cost savings values and computation time.Findings: Findings indicated that for the constrained problem, GA has a better performance than PSO. Accordingly, for an unconstrained problem, by using the derivative of the profit function and performing sensitivity analysis, the influence of parameters such as demand, price, holding cost after the price increase, λ in exponential distribution, length of periods in uniform distribution, and deterioration rate on the decision variables including order quantity and the profit were obtained,Practical implications: The model’s generated policy is more effective and profitable for retailers when demand and deterioration rate are higher and replenishment periods are decreased.Originality/value: This study completes the previous inventory control models that were under the policy of known price increase and is closer to the real environment by utilizing deteriorating items, capacity constraints, and meta-heuristic approaches.
خلاصه ماشینی:
(Research Paper) Optimizing the inventory control decisions under multiple constraints for deteriorating products: An application of meta-heuristic algorithms Narges Mehmandost Department of Management, Faculty of Administrative Sciences & Economics, University of Isfahan, Isfahan, Iran, narges.
Accordingly, for an unconstrained problem, by using the derivative of the profit function and performing sensitivity analysis, the influence of parameters such as demand, price, holding cost after the price increase, λ in exponential distribution, length of periods in uniform distribution, and deterioration rate on the decision variables including order quantity and the profit were obtained, Practical implications: The model’s generated policy is more effective and profitable for retailers when demand and deterioration rate are higher and replenishment periods are decreased.
Therefore, retailers must decide on their inventory based on the increased rate of product prices in the coming months, random time to the next savings, amount of deterioration items, warehouse capacity and use the optimal use of the special order provided by the supplier (Zhang, X.
L & Shi (2018), Janssen (2018b), Tashakkor, Mirmohammadi, & Iranpoor (2018), Li & Teng (2018), Asif and Biswajit (2018), Bounkhel et al.
Ouyang (2016), Palanivel, Uthayakumar & Finite (2015), Herbon (2017), Banerjee & Agrawal (2017), Herbon & Khmelnitsky (2017), Jaggi, Tiwari & Goel (2017), and Kaya & Ghahroodi (2018), considered various situations to obtain optimal order quantity for deteriorating items under changing prices.
, 2014; Buhnia, Shaikh & Gupta, 2015; Bhunia & Shaikh, 2015; Vandani, Niaki, & Aslanzade, 2017; Akbari Kaasgari, Imani, & Mahmoodjanloo, 2017; Azadeh, 2017; Hiassat, Diabat & Rahwan, 2017; Tiwari, 2017).
, 2014; Buhnia, Shaikh & Gupta, 2015; Bhunia & Shaikh, 2015; Vandani, Niaki, & Aslanzade, 2017; Akbari Kaasgari, Imani, & Mahmoodjanloo, 2017; Azadeh, 2017; Hiassat, Diabat & Rahwan, 2017; Tiwari, 2017).