PRICE AND LEAD TIME DECISION MODEL DEVELOPMENT USING PARTICLE SWARM OPTIMIZATION ALGORITHM IN MAKE TO ORDER SYSTEM FOR FASHION INDUSTRY
This research focuses on selling fashion products using the MTO production system or known as the Pre-Order (PO) sales strategy. Often, PO sales were chosen to avoid deadstock phenomenon due to rapid changes of tren without considering the suitability of the product with the chosen strategy, thus...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/63882 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | This research focuses on selling fashion products using the MTO production system
or known as the Pre-Order (PO) sales strategy. Often, PO sales were chosen to
avoid deadstock phenomenon due to rapid changes of tren without considering the
suitability of the product with the chosen strategy, thus impacting in low demand.
One of the research objectives is to develop a prediction model of PO/non-PO sales
strategy based on 12 input variabels that explain the product characteristics. The
method used is a hybrid Artificial Neural Network (ANN) and logistic regression,
called ANN-Plogit. Logistic regression used to determine the significance of each
predictor to the target and the ANN model used as predictions. Evaluation of model
performance is based on error rate (MSE) and confusion matrix. The result is the
model of ANN-Plogit 6 variabels has the best performance with the lowest
prediction error and the highest prediction accuracy.
In the application of MTO, the amount of lead time is a crucial decision which is
often compensated by a lower price in order to obtain an increase in the number of
demands. This research also discusses the pricing and lead time decision model in
the MTO system by considering the policy of minimum order quantity (MOQ) that
set by the production vendors. This condition allows for inventory costs even for
MTO production. The decision variabels are price and lead time as well as the
number of demands that optimized simultaneously to maximize sales profit. The
solution search is carried out using a metaheuristic approach, the Particle Swarm
Optimization algorithm is chosen because of its simplicity and the computation time
tends to be short. Based on a search with the PSO Algorithm, the price of 324,750
and a lead time of 9 days considered as the best solution with a maximum profit of
IDR 80,526,000. Through the validation of the results, this decision is considered
feasible to be applied as pre-order sales in terms of market preferences.
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