A decision support system for agricultural machines and equipment selection: A case study on olive harvester machines

Autor: Aida Hami-Dindar, Ashkan Hafezalkotob, Naghmeh Rabie, Arian Hafezalkotob
Rok vydání: 2018
Předmět:
Zdroj: Computers and Electronics in Agriculture. 148:207-216
ISSN: 0168-1699
DOI: 10.1016/j.compag.2018.03.012
Popis: Olive is considered as one of the most important and useful products, but the traditional harvesting methods are failing to fulfill the current need; therefore, it is crucial to make the olive harvesting mechanized. In order to expedite the olive harvesting mechanization process, the engineers have designed various machines and equipment, which have their own special advantages. Now, the main challenge is to select the best olive harvesting machine to develop and improve the economic conditions in agricultural field to maintain the food demand. In the present study, we intend to present a decision support system to aid decision-making about olive harvesting machines. To achieve this target, we evaluate six candidate machines with nine important criteria and classify them into three groups: beneficial, non-beneficial, and target-based criteria. For weighting the criteria, the best-worst method is applied, and because of having target criterion in the selection problem, the decision matrix is normalized by the target-based technique. Finally, using two proposed methods, target-based MULTIMOORA and WASPAS, we select the best harvesting machine. In addition, we employ dominance method to integrate the resultant rankings of harvesting machines.
Databáze: OpenAIRE
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