7654

7126

كارشناسي ارشد

سيستم هاي اقتصادي-اجتماعي

اصفهان: دانشگاه صنعتي اصفهان، دانشكده صنايع و سيستم ها

1391

نه،75ص.: مصور،جدول،نمودار

ص.ع.به فارسي و انگليسي

ناصر ملاوردي

28/1/92

علي شاهنده، فريماه مخاطب رفيعي

مهندسي صنايع و سيستم ها

ID7126

به فارسي وانگليسي: قابل رويت در نسخه ديجيتالي

Inventory Management in Service Parts Logistics Systems Sobhan Soheili s soheili@in iut ac ir Date of Submission 2012 12 20 Department of Industrial and Systems Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Naser Mollaverdi naserm@cc iut ac ir Abstract Network design is one of the important and basic issues of supply chain and logistics because the other planning activities and related issues are affected by the network general layout This importance in service parts logistics systems is much more due to the high price high costs of equipment downtime and the necessity of representing quick services to customers Therefore network designers and decision makers are always looking for a model which consider maximum influential factors in this issue and provide the best decisions by simultaneously considering them In this paper we represent a mix integer mathematical programming model that simultaneously considers facility location the amount of inventory of each part in each facility assignment of customers to facilities and transportation mode of each order to its customer and finally take the best decisions Moreover there is a service level constraint for each facility that ensures a certain time based service level Also when a facility is out of stock of any part this model allows it to satisfy its assigned customer s orders by an emergency shipment from the central warehouse Considering the complexity and largeness of solution for this problem a genetic algorithm has been used for solving the proposed model For solving the proposed model by the mentioned method initial data has been produced randomly with suitable distributions by considering the qualitative data from similar studies and real world Finally the proposed model has been solved by GAMS software in small size and by genetic algorithm in small medium and large size Also the final results from these two methods have been compared with each other in small problems and sensitivity analysis has been done on time based service level Keywords Service Parts Logistics Emergency Lateral Transshipments Time based Service Level Genetic Algorithm

ناصر ملاوردي

علي شاهنده، فريماه مخاطب رفيعي