Solving Order Planning Problem Using a Heuristic Approach: The Case in a Building Material Distributor

For building material distributors, order planning is a key process as a result of the increase in construction projects’ scale and complexity. In this paper, the integration of simulation modeling and the response surface methodology (RSM) is presented to solve an order planning problem in the cons...

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Bibliographic Details
Main Authors: Chia-Nan Wang, Ngoc-Ai-Thy Nguyen, Thanh-Tuan Dang
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/24/8959
Description
Summary:For building material distributors, order planning is a key process as a result of the increase in construction projects’ scale and complexity. In this paper, the integration of simulation modeling and the response surface methodology (RSM) is presented to solve an order planning problem in the construction supply chain. The interactions of various factors are examined to observe their effects on key system measurements, and a combination of factor levels is determined to achieve the optimal performance. RSM is applied to find the possible values of the optimal setting for system responses, which consists of three main steps: central composite design (CCD), Box–Behnken design (BBD), and a comparison of both designs. The model is tested with a realistic case study of a building material distributor in Vietnam to demonstrate its effectiveness. Controllable factors (independent variables), which are the review period (T), order quantity (Q), and safety stock (SS), are found to significantly affect system responses, which are the total cost (TC) and customer service level (CSL). The results provide the best settings of factor levels that produce the possible minimum TC and maximum CSL. The developed framework could be applied as a useful reference for decision-makers, purchasing managers, and warehouse managers to obtain the most suitable order policy for a robust order planning process.
ISSN:2076-3417