Selecting wood supply contracts under uncertainty using stochastic programming. Issue 2 (3rd May 2021)

• Record Type: Journal Article
• Authors: Rahimi, Ali; Rönnqvist, Mikael; LeBel, Luc; Audy, Jean-François
• Is Part Of: Infor. Volume 59:Issue 2(2021)
• Page Start: 191
• Page End: 211
• Publication Date: 2021-05-03
• Subjects: Stochastic programming -- wood supply procurement -- contract selection -- portfolio strategy; Operations research -- Periodicals; Electronic data processing -- Periodicals; Systems engineering -- Periodicals; Systems engineering; Electronic data processing; Periodicals; 003.05
• DOI: 10.1080/03155986.2020.1800975
• Languages: English
• ISSNs: 0315-5986

Abstract

Abstract: A large portion of expenses in the forest industries is associated with wood supply procurement. Numerous suppliers are involved and securing wood supply contracts with competitive prices is a constant challenge for procurement managers. A major difficulty is the procurement exposure to various sourcing risks including the start of the spring thaw, contract breach, or unreliability of suppliers. A procurement plan should anticipate random events and include measures that counter their negative impact. Recourse actions must be planned by considering volume uncertainty and wood price fluctuations. Relying on manual tools is hardly capable of considering all aspects of this problem. A stochastic programming approach is proposed to support the development of a procurement plan. In this model, several types of contracts including fixed, flexible and option contracts with different durations are included. The proposed selection of contracts from a stochastic programming model yields average optimality in the presence of plausible scenarios. The developed two-stage stochastic programming model decides on the selection of the optimal portfolio of contracts to minimize total procurement costs. Based on a case study in Quebec, an average saving of 4% was shown by using stochastic programming compared to the deterministic approach.