Seyed Hossein Razavi Hajiagha; Hadi Akrami; Shide Sadat Hashemi
Volume 11, Issue 31 , January 2014, , Pages 35-53
Abstract
Master production scheduling is a midterm phase in planning which translates the long term aggregate production planning to a plan which determines the scheduling and magnitude of different products production. This problem requires investigating a wide range of parameters about demand, manufacturing ...
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Master production scheduling is a midterm phase in planning which translates the long term aggregate production planning to a plan which determines the scheduling and magnitude of different products production. This problem requires investigating a wide range of parameters about demand, manufacturing resource usage and costs. Uncertainty is an intrinsic characteristic of these parameters. In this paper, a model is developed for master production scheduling under uncertainty where demands are considered as stochastic variables, while cost and utilization parameters are expressed as fuzzy numbers. A hybrid approach is also proposed to solve the extended model. The application of the proposed method is examined in a numerical example.
Naser Hamidi; Parvaneh Samouei; Mahdi Eghbali
Volume 8, Issue 20 , March 2011, , Pages 195-214
Abstract
Identification and determination of products and their quantities according to available resources are called Product Mix Problem in manufacturing plants. There are many methods for solving these problems. One of these methods is Theory of Constraints which is easy to use and understand. But unfortunately, ...
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Identification and determination of products and their quantities according to available resources are called Product Mix Problem in manufacturing plants. There are many methods for solving these problems. One of these methods is Theory of Constraints which is easy to use and understand. But unfortunately, it can’t solve multi bottleneck problems, so it doesn’t have sufficient efficiency when introduce new product. Consequently Revised Theory of constraints was proposed to solve these problems. This is one of the best methods that provide the same results as ILP in most of the cases. But in this algorithm all parameters are certainty. However, in the real-world, such parameters like capacity and demands are uncertainty. In this situation, fuzzy set theory can be used as an effective tool. So In this paper, an algorithm based on RTOC and fuzzy logic is proposed for solving Product Mix Problems with fuzzy capacity and fuzzy demand. This algorithm is more flexible and popularized than other methods which arc used for solving fuzzy product mix problems.
