TITLE:
Supply Chain Network Optimization of the Canadian Forest Products Industry: A Critical Review
AUTHORS:
Shashi Shahi, Reino Pulkki
KEYWORDS:
Agent-Based Optimization; Discrete-Event Simulation; Forest Products Industry; Two-Way Information Flow; Uncertainty
JOURNAL NAME:
American Journal of Industrial and Business Management,
Vol.3 No.7,
November
29,
2013
ABSTRACT:
The Canadian forest products industry
has failed to retain its competitiveness in the global markets because of the under-utilization
of its resources. Supply chain optimization models can identify the best
possible fibre utilization strategies from multiple options of value creation
based on fluctuating market conditions in the forest industries. This paper
comprehensively reviews the literature related to supply chain models used both
in general and specifically in the forest products industry. The optimization
models use information from multiple agents (market demand attributes, flexible
wood procurement and manufacturing processes, and resource characteristics),
and share this information at each level in the supply chain network. However,
the modeling of two-way flow of information (market to forests and vice-versa)
for order promising and demand fulfillment through all facilities including
manufacturing, processing, raw material procurement and inventory control is
missing. The studies that focus on optimization are mostly deterministic in
nature and do not account for uncertainty both in supply of raw materials and
demand of forest products. Simulation and optimization models have been
independently used for supply chain management in the past. The literature
lacks an integrated approach that combines simulation and optimization models
throughout the supply chain network of the Canadian forest products industry.
Further studies should focus on developing simulation-based optimization models
that will help in providing an operational planning tool that meets industrial
expectations and provides much better solutions than current industrial
practice.