چكيده به لاتين
Abstract:
Aggregate production planning (APP) determines the best way to satisfy customer’s demand in the time horizon of 6-18 months in the future through setting the production rate in regular times, overtimes, inventory levels, subcontracting and other control variables. Development of manufacturing companies as well as increasing diversity of products, have placed the companies in chain of suppliers. In such circumstances, the entire supply chain needs a single APP.
This thesis specifies an APP within the supply chain for the production of products with a very limited expiration date, such as yearbooks, calendars and seasonal clothing using postponement policy under uncertainty. In order to apply the concept of postponement for these products, three types of production activities including final production, work in process (WIP) production and final assembly are taken into account. Additionally, a robust optimization approach is used to control the inherent uncertainty of the demand and cost parameters.
The concerned supply chain is a competitive three-level one; so the presented model is a bi-level programming model. The Stackelberg game concept is used for the competition, where at high level, the leader is looking to maximize its profit and in the lower level, followers are looking to maximize their income. After converting two-level model to a single-level, since the problem is NP-hard and for dealing with computational complexity in the large dimensions, the exact Bender’s Decomposition algorithm is used. “NIK Calendar” company data located in Tehran are used to validate the model and demonstrate the effectiveness of the proposed Bender’s algorithm. Therefore, the proposed model is derived from real situations and is presented to solve the production planning problem of this company. After running the model and analyzing the results, insights are presented for improving the production. The computational results clearly show efficiency and applicability of the proposed model and algorithm.
Keywords: Robust Optimization, Aggregate Production Planning, Very Limited Expiration Date, Bender’s Decomposition Algorithm, Bi-Level Programming.
