A stochastic programming approach for sawmill production planning
type: Item
instance of: scholarly article
title: A stochastic programming approach for sawmill production planning
zbMATH Open document ID: 1390.90374
DOI: 10.1504/IJMOR.2013.050604
author: Xianqiang Yang
published in: International Journal of Mathematics in Operational Research
publication date: 2018-05-29T00:00:00Z
review text: Summary: This paper investigates a sawmill production planning problem where the non-homogeneous characteristics of logs result in random process yields. A two-stage stochastic Linear Programming (LP) approach is proposed to address this problem. The random yields are modelled as scenarios with discrete probability distributions. The solution methodology is based on the sample average approximation method. Confidence intervals are constructed for the optimality gap of several candidate solutions, based on Common Random Number (CRN) streams. A computational study including a prototype sawmill is presented to highlight the significance of using the stochastic model instead of the mean-value deterministic model, which is the traditional production planning tool in sawmills.
Mathematics Subject Classification ID: 90B80
Mathematics Subject Classification ID: 90C15
Mathematics Subject Classification ID: 90C05
zbMATH DE Number: 6876004
zbMATH Keywords: production planning
zbMATH Keywords: random yield
zbMATH Keywords: sawmill
zbMATH Keywords: stochastic linear programming
zbMATH Keywords: sample average approximation
MaRDI profile type: Publication
full work available at URL: ijmor.2013.050604
OpenAlex ID: W2073917096
description: scientific article; zbMATH DE number 6876004