Multi-commodity supply network planning in the forest supply chain

Chauhan, Satyaveer Singh; Frayret, Jean‐Marc; LeBel, Luc

doi:10.1016/j.ejor.2008.03.024

Cited by 33 publications

(26 citation statements)

References 17 publications

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“…Furthermore, forest planning is performed in a stochastic environment without high quality information. This is due to the fact that information collection in this area, such as trees diameter, species, dimension and location of internal nodes, among others, is complex and expensive (Chauhan et al, 2009).…”

Section: Forest-based Supply Chainmentioning

confidence: 99%

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

et al. 2015

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Aim of study: This work aims to provide an overview of Model Predictive Controllers (MPC) applications in supply chains, to describe the forest-based supply chain and to analyse the potential use and benefits of MPC in a case study concerning a biomass supply chain.Area of study: The proposed methods are being applied to a company located in Finland.Material and methods: Supply chains are complex systems where actions and partners’ coordination influence the whole system performance. The increase of competitiveness and need of quick responses to the costumers implies the use of efficient management techniques. The control theory, particularly MPC, has been successfully used as a supply chain management tool. MPC is able to deal with dynamic interactions between the partners and to globally optimize the supply chain performance in the presence of disturbances. However, as far as is authors’ knowledge, there are no applications of this methodology in the forest-based supply chains. This work proposes a control architecture to improve the performance of the forest supply chain. The controller is based on prediction models which are able to simulate the system and deal with disturbances.Main results: The preliminary results enable to evaluate the impacts of disturbances in the supply chain. Thus, it is possible to react beforehand, controlling the schedules and tasks’ allocation, or alert the planning level in order to generate a new plan.Research highlights: Overview of MPC applications in supply chains; forest-based supply chain description; case study presentation: wood biomass supply chain for energy production; MPC architecture proposal to decrease the operation times.Keywords: biomass; forest; Model Predictive Control; planning; supply chain.

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Section: Forest-based Supply Chainmentioning

confidence: 99%

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

et al. 2015

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“…In order to assess the economic feasibility of bioenergy production at the AGS, it is important to understand and improve the efficiency of the woody biomass supply chain from the forest management units (FMUs) surrounding it. There has been little published research on improving the efficiency of woody biomass supply chains [12], due to the lack of availability of real data and appropriate methodologies for assessing woody biomass availability [12]. A few studies, that address the biomass supply chain management problem in the forestry sector, have only focused on a single aspect of the problem [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…A few NLDP models have been developed for harvesting and transporting agricultural residue for bioenergy production in different parts of the world: United States [32][33][34], Brazil [35], Netherlands [36,37] and Europe [38]. Studies in Canada mostly focused on optimizing harvesting and transportation of raw material for forest products industries [12,[39][40][41][42][43]. Since woody biomass is usually scattered over a large geographic area, its supply chain modeling requires accurate information about its location and availability [44,45].…”

Section: Introductionmentioning

confidence: 99%

“…The problem with the LP modeling approach is that it over-simplifies complex problems into simple linear equations and cannot optimize problems where decision variables are constrained to have only integer values. In order to account for both discrete as well as continuous decision variables for optimizing supply logistics, mixed-integer programming (MIP) models are used [12,[26][27][28]. The use of MIP models in bioenergy production has been further extended by formulating mixed integer linear programming (MILP) models to optimize the design of supply networks based on financial criteria [29,30].…”

Section: Introductionmentioning

confidence: 99%

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Modeling Woody Biomass Procurement for Bioenergy Production at the Atikokan Generating Station in Northwestern Ontario, Canada

et al. 2012

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Efficient procurement and utilization of woody biomass for bioenergy production requires a good understanding of biomass supply chains. In this paper, a dynamic optimization model has been developed and applied to estimate monthly supply and procurement costs of woody biomass required for the Atikokan Generating Station (AGS) in northwestern Ontario, based on its monthly electricity production schedule. The decision variables in the model are monthly harvest levels of two types of woody biomass, forest harvest residues and unutilized biomass, from 19,315 forest depletion cells (each 1 km 2 ) for a one year planning horizon. Sixteen scenarios are tested to examine the sensitivity of the cost minimization model to changing economic and technological parameters. Reduction in moisture content and improvement of conversion efficiency showed relatively higher reductions in monthly and total costs of woody biomass feedstock for the AGS. The results of this study help in understanding and designing decision support systems for optimal biomass supply chains under dynamic operational frameworks.

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“…Most of the existing studies probe either biomass supply (Freppaz et al 2006, Gan 2007 or logistics (Gunnarsson et al 2003, Frombo et al 2009, Kim et al 2011 or both (Sokhansanj et al 2006). Supply chains for multiple final products have also been analyzed (Chauhan et al 2009). Among the studies on biomass/bioenergy logistics are analyses of techno-economic aspects (particularly facility siting) of bioenergy supply chains using various methods, including mathematic programming and spatial analysis tools (He and Zhang 2010, Rentizelas and Tatsiopoulos 2010, Tittmann et al 2010.…”

Section: Introductionmentioning

confidence: 99%

Biomass Utilization Allocation in Biofuel Production: Model and Application

Smith¹

2012

International Journal of Forest Engineering

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Multi-commodity supply network planning in the forest supply chain

Cited by 33 publications

References 17 publications

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

Overview of MPC applications in supply chains: Potential use and benefits in the management of forest-based supply chains

Modeling Woody Biomass Procurement for Bioenergy Production at the Atikokan Generating Station in Northwestern Ontario, Canada

Biomass Utilization Allocation in Biofuel Production: Model and Application

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