بهینه ‌سازی سطح موجودی قطعات یدکی خودروهای نظامی با استفاده از توزیع احتمال ترکیبی

هدف از این تحقیق، بهینه‌سازی سطح موجودی قطعات یدکی خودروهای نظامی با استفاده از توزیع احتمال مختلط است. این روش شامل طراحی یک مدل بر‌اساس توزیع احتمال مختلط و استفاده از یک الگوریتم ژنتیک برای حل آن است. ارزیابی هزینۀ سیستم بهینه و کمیت سفارش اقتصادی، نشان داد که مقرون به‌صرفه‌ترین مقادیر در تکرارهای اول، چهارم و دهم به دست آمد. تجزیه و تحلیل حساسیت نشان داد که مدل هزینۀ بهینه به تمام پارامترهای بررسی‌شده به زمان لجستیک، بیشترین تاثیر و هزینۀ هر واحد موجودی کمترین حساس بود. یافته‌ها نشان می‌دهد ‌مقدار سفارش بهینه بر‌اساس حداقل هزینه است و در‌نهایت بهترین مقدار سفارش‌ در ابتدای راه‌حل مدل، تعیین می‌کند که ازنظر هزینه بهینه بود. با تغییر پارامترها، مقدار سفارش بهینه، شناسایی شد.

spare parts inventory optimization for military vehicles using a mixed probability distribution

purpose: in general, inventory optimization is one of the most important techniques in the production system, because the high cost of an empty warehouse and the cost of losing customers can cause serious damage to a system. the basic idea for inventory is to provide flexibility for a system and protect the system against events such as stock out. inventory capacity for each product or part is defined by demand, delivery time and part price. by balancing the supply and demand rates, the optimal inventory capacity can be achieved. it is necessary to use practical and effective techniques and solutions to reduce breakdowns to optimally use existing equipment and resources and reduce large costs in terms of energy wastage and repairs and repurchase of equipment. in this context, spare parts are one of the most important links in performing optimal maintenance and repairs and quickly returning equipment to the production line. in good management of spare parts, the inventory system of the warehouse will lead to the reduction of maintenance and repair costs, manpower and the duration of equipment failure and will ultimately help to increase productivity. this study aims to optimize the inventory level of spare parts for military vehicles using a mixed probability distribution.                                                           design/methodology/approach: first, based on the literature review and selected basic articles, the research gaps have been identified, and accordingly, a mathematical model has been developed and solved to optimize the spare parts of military vehicles. then, a meta-inventive method has been used to solve the problem. this is because the use of meta-heuristic methods to check and analyze the sensitivity of inventory optimization models can lead to better and more accurate results, and also the use of these methods is relatively new and helps in solving optimization problems. also, the problem studied in this research is a non-linear integer programming model, which has been used for the problems of medium and large dimensions due to the complexity of the problem. the meta-heuristic method based on the genetic algorithm has been applied to save the total costs. finally, to prove the effectiveness of the model, the proposed model has been implemented in a case study on the parts of military vehicles in the 177th brigade of torbet heydarieh.