ارايه‌ي يك الگوريتم ابتكاري براي حل مسيله‌ي يك‌پارچه‌ي توليد تركيبي ـ برون‌سپاري تحت نظريه‌ي محدوديت ها

Presenting a Heuristic Algorithm for Integrated Product Mix-Outsourcing Problem under Theory of Constraint

امروزه سيستم هاي توليدي با هدف دست‌يابي به سود بيشتر، سعي مي كنند سهم بيشتري از تقاضاي بازار را ارضا كنند. اما در اكثر موارد به‌دليل ناكافي بودن منابع توليدي مايل‌اند برخي محصولات را از منابع خارجي تهيه ‌كنند. با توجه به اين مهم، مسيله‌ي توليد تركيبي با مفهوم تصميم‌گيري برون‌سپاري ادغام مي‌شود و مسيله‌ي يك‌پارچه توليد تركيبي ـ برون‌سپاري (IPMO) مطرح مي‌‌شود. پرسش اصلي در اين مسيله آن است كه چه مقدار از هر محصول داخل سيستم توليد ‌شود و چه مقدار از آن برون‌سپاري شود. يكي از معروف‌ترين روش‌هاي حل مسيله‌ي IPMO، روش نظريه‌ها (TOC) است. در اين تحقيق روشي ابتكاري و ساده براساس TOC براي حل مسيله‌ي IPMO در حالت چندگلوگاهي ارايه مي شود. الگوريتم پيشنهادي با الگوريتم‌هاي موجود در ادبيات مورد مقايسه قرار مي گيرد و نشان داده مي شود كه الگوريتم پيشنهادي قادر به دست‌يابي به جواب-هاي مناسب است.

Determining the production rate of each product in order to maximize the throughput is important for production systems. This problem is called the product mix (PM) problem. In most cases, due to insufficient production resources, companies tend to obtain some of their products from external resources. Given this, PM, with the decision to outsource production, a combined and integrated product mix-outsourcing problem (IPMO) is formed. Here, the main question is how much of each product should be produced internally and how much should be outsourced. One of the most famous methods for solving the IPMO problem is the theory of constraints (TOC). TOC offers a five step methodology for the identification of organizational constraints and their elevation. The methodology is described as follows: (1) Identify the system’s constraint(s) (2) Decide how to exploit the system’s constraint(s) (3) Subordinate everything else to the above decision (4) Elevate the system’s constraint(s), and (5) If, in the previous steps, a constraint has been broken, go back to step1. In step1, the system bottleneck is identified. In step 2, the scheduler decides how to use the bottleneck in order to maximize the throughput. In step 3, the bottleneck schedule (drum) is developed and, through backward and forward scheduling, other work centers are scheduled. In step 4, necessary improvements are considered in order to promote the bottleneck performance. And, finally, step 5 indicates the dynamic nature of the TOC. The product mix is determined through the first two steps of the TOC. In this study, we will introduce a simple and heuristic method based on TOC to solve IPMO problems in multi-bottleneck mode. First, it is shown, by an example, that available heuristic algorithms for solving the IPMO problem do not necessarily lead to optimum and even feasible solutions. Then, the proposed algorithm is compared with existing methods in the literature in single and multi-bottleneck modes, and it is indicated that the proposed algorithm is able to achieve appropriate solutions.