Multicriteria Decision Making Methods—A Review and Case of Study

García-Alcaráz, Jorge Luis; García-Alcaraz, Pedro; Aryanfar, Yashar; Realyvásquez-Vargas, Arturo; Mohtaram, Soheil; Haj-Assad, Mamdouh El

doi:10.1007/978-3-031-08246-7_10

Cited by 2 publications

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The application of AHP has been rather broad, including ranking, evaluation, allocation, cost-benefit analysis, forecasting, and strategic decision settings [64,67,68]. It is among the most widely used MCDA techniques in general [64,[69][70][71][72][73] as well as for natural resource and energy management problems [73][74][75] and in energy transition studies investigating barriers to development, such as biorefinery transition in the European pulp and paper industry [76], renewable energy adoption in Pakistan [77], barriers to hydrogen fuel cell energy production in South Korea [78], and forest biomass for heating in Quebec [79]. Other studies have used AHP, often combined with other analytic techniques, to assess investment or policy decisions on alternative energies in Saudi Arabia [80] and renewable energy in transport policies in Europe [81,82].…”

Section: Introductionmentioning

confidence: 99%

Towards a Bioeconomy: Supplying Forest Residues for the Australian Market

Garvie,

Lee,

Kulišić

2024

Energies

View full text Add to dashboard Cite

Australia has abundant volumes of forest residues that are a potential feedstock for supplying biomass as a renewable carbon carrier to the market. However, there remains an underutilization of this resource, even in mature bioeconomy markets. Several existing or perceived barriers can be attributed to the underdeveloped, forest-based bioeconomy in Australia. One of these is the limited understanding of feedstock supply costs. In this study, two ranking approaches were applied to identify the optimal biomass feedstock supply chain from field to conversion plant gate. A panel of experts embedded in the Australian bioeconomy were employed to first assign ranks to biomass supply chain items by cost intensity. Then, a layer of analytic hierarchical process (AHP) was used to weigh and rank various biomass supply pathways by efficiency. The results reveal that biomass extraction ranks the highest and biomass feedstock storage ranks the lowest, relative to other supply chain costs. Extracting and chipping material in the field attracted the most support from the experts in terms of efficiency, followed by transporting and chipping at the roadside and, finally, transporting and chipping at the conversion plant. This study provides insights for designers of the forest-based bioeconomy in Australia into relative cost drivers that may be applied to investment and industry decisions. It also provides a framework to support further investigations into forest biomass development and the management of biomass as a renewable carbon carrier at a time when Australia is transitioning from an energy policy focused on fossil fuels to a renewable energy strategy.

show abstract

Section: Introductionmentioning

confidence: 99%

Towards a Bioeconomy: Supplying Forest Residues for the Australian Market

Garvie,

Lee,

Kulišić

2024

Energies

View full text Add to dashboard Cite

show abstract

Hybrid decision-making in atmospheric plasma spraying enables human–machine teaming

Bocklisch,

Grimm

et al. 2024

Int J Adv Manuf Technol

View full text Add to dashboard Cite

With the development of human-cyber-physical-production systems in intelligent manufacturing, cyber-supported production based on artificial intelligence is becoming an increasingly powerful means of controlling machines and collaborating with human users. Semi-autonomous systems with a medium degree of automation enable human-centered, flexible, and sustainable production, for instance, in hybrid decision-making. Especially in applications that do not meet the requirements for full automation and when humans are to be involved in their role as qualified decision-makers, teaming-capable systems are desirable and offer considerable advantages. This paper outlines the transdisciplinary concept of human–machine teaming and the role of human cognition in engineering tasks with multi-criteria decision-making. An illustrative real-life example from thermal spray technology is used to show how explainable artificial intelligence models offer targeted, hybrid cyber decision support. This new approach based on fuzzy pattern classifiers combines expert knowledge- and data-based modeling and enables a transparent interpretation of the results by the human user, as shown here using the example of test data from atmospheric plasma spraying. The method outlined can potentially be used to provide hybrid decision support for a variety of manufacturing processes and form the basis for advanced automation or teaming of humans and cyber-physical-production systems.

show abstract

Multicriteria Decision Making Methods—A Review and Case of Study

Cited by 2 publications

References 37 publications

Towards a Bioeconomy: Supplying Forest Residues for the Australian Market

Towards a Bioeconomy: Supplying Forest Residues for the Australian Market

Hybrid decision-making in atmospheric plasma spraying enables human–machine teaming

Contact Info

Product

Resources

About