Development of a decision support tool for optimizing the short-term logistics of forest-based biomass

Malladi, Krishna T.; Quirion-Blais, Olivier; Sowlati, Taraneh

doi:10.1016/j.apenergy.2018.02.027

Cited by 32 publications

(16 citation statements)

References 30 publications

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“…Nevertheless, forest transportation planning is not only limited to timber production. For example, Kar and Jacobson (2012), Zamora-Cristales and Sessions (2013), Zamora-Cristales et al (2015), Zamora-Cristales et al (2017), Chen et al (2017), Malladi et al (2018), Akhtari et al (2018) and Alvarez-Miranda et al (2019) put an effort to optimize forest transportation to relocate biomass to be utilized as a source of energy at a demand area. Evans (2007) and Naik et al (2010) clarified that energy from biomass is important to create biofuel energy and biofuel product.…”

Section: General Backgroundmentioning

confidence: 99%

Bees algorithm for Forest transportation planning optimization in Malaysia

Jamaluddin

Norizah

Hasmadi

et al. 2021

Forest Science and Technology

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Algorithm is widely used in various areas due to its ability to solve classes of problems. Due to multiple objectives to be met and varied algorithm application in this digital era, addressing the problem-solving optimization in a more efficient and effective way has become more reasonable. Forest transportation planning is one of the most expensive activities in timber harvesting and can be optimized through algorithm application. Forest transportation planning is a vital component of timber harvesting activities. Inappropriate planning may raise the overall costs of harvesting activities. This paper aims to give an overview of several algorithm application in optimizing the forest transportation planning problem and give an insightful information regarding the relationships between algorithm and the integration of transportation system characteristics and variables. Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. Although no literature was found regarding forest transportation planning problem optimization with regards to Bees Algorithm (BA), rules set for several transportation problem evidenced from literature search seems to be applicable to forestry. Generally, in this paper, the BA has been given focus for forest transportation planning problem optimization as a potential algorithm to overcome the challenges of environmental degradation and efficiency of timber extraction used, as well as its accuracy and less processing time for problem-solving.

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Section: General Backgroundmentioning

confidence: 99%

Bees algorithm for Forest transportation planning optimization in Malaysia

Jamaluddin

Norizah

Hasmadi

et al. 2021

Forest Science and Technology

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“…As shown in Figure 7, the main sources of RE focused on in articles developed in high-income countries (Austria, Canada, Finland, Italy, USA, etc.) are biomass [111][112][113][114][115], wind-solar [116][117][118], and biodiesel [104,110,119]. Although the same renewable energies are focused on in countries with the same level of development, the research objectives are quite different.…”

Section: Level Of Countries' Development Focused On In the Papers And...mentioning

confidence: 99%

Renewable Energy and Sustainability from the Supply Side: A Critical Review and Analysis

Azevedo¹,

Sequeira²,

Santos³

2020

Applied Sciences

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This article provides a critical review of the literature on the relationship between renewable energies and sustainability considering the three dimensions of sustainability: economic, social, and environmental. First, a bibliometric tool is used and then a more in-depth analysis of selected literature is performed, focusing on the type of renewable energy analyzed and the level of development of countries, the dimension of sustainability focused on and the country’s development level, and the type of renewable energies focused on and the dimension of sustainability analyzed. It represents a milestone in the topic giving insights on the state of the art of the research on this research area, enhancing empirical evidence on the kind of relationships and developing a discussion on how closely aligned the political and institutional discourses are with the research concerns. We conclude that, while studies on lower-income countries focus on lower-rung energies, studies on higher-income countries focus on the study of more diversified sources. Moreover, wind–solar energy is the most reported in the articles concerned with environmental sustainability. Our main recommendation is to further investigate the implementation of modern renewable energies in developing countries, to help those countries to climb the energy ladder toward cleaner energy supply.

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“…D'Amours et al [7] noted that "operational planning is really the planning process that fixes how and when the value will be captured". In spite of this, a very limited number of operational level FBSC planning models have been published [8], the majority of which deal with transport scheduling and routing, for example, [9] and [10].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Operational-Level Forest Biomass Logistic Costs for Storage, Chipping and Transportation through Roadside Drying

Strandgard

Turner

Shillabeer

2022

Forests

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Forest biomass (FB) could supply more of Australia’s energy needs, but delivered costs must be reduced for it to be a viable energy source. Operational planning is critical to reducing delivered costs as it determines actual activities, though few operational FB supply chain (FBSC) planning tools have been published. This paper presents a “proof-of-concept” operational FBSC decision support system (DSS) to schedule FB deliveries for eight weeks from roadside storage for the least cost, taking in account moisture content changes. Four mathematical models are compared, solving a linear formulation of the FB delivery problem in terms of solution speed and delivered cost, and the practicality of implementing the solutions. The best performing model was a Greedy algorithm as it produced solutions not significantly different from those of the tested linear programming solver and was readily modified to significantly improve solution implementation through the addition of a non-linear element. FBSC planning tools typically assume accurate knowledge of stored FB quantities and that little or no rainfall occurs during storage. In practice, stored FB quantity estimates can be inaccurate due to variation in the bulk density of the piles. Improving these estimates is a critical area for future research. This study found that simulated rainfall with <20 mm during the first week of the scheduled period did not significantly effect delivered costs.

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Development of a decision support tool for optimizing the short-term logistics of forest-based biomass

Cited by 32 publications

References 30 publications

Bees algorithm for Forest transportation planning optimization in Malaysia

Bees algorithm for Forest transportation planning optimization in Malaysia

Renewable Energy and Sustainability from the Supply Side: A Critical Review and Analysis

Optimizing Operational-Level Forest Biomass Logistic Costs for Storage, Chipping and Transportation through Roadside Drying

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