Forklift selection by multi-criteria decision-making methods
DOI:
https://doi.org/10.15587/1729-4061.2023.285791Keywords:
forklift selection, MCDM method, COCOCO method, PIV method, weight methodAbstract
A forklift is a very important and common equipment for transporting materials in many different locations such as workshops, warehouses, supermarkets, etc. This equipment has the effects of reducing labor consumption of workers, ensuring the safety of goods and improving labor efficiency. That is why forklift selection is very important. In order to choose a forklift, it is necessary to consider many parameters such as lifting capacity, lifting height, travel speed, safety level, price, maintenance cost, level of impact on the environment, ease of use, etc. However, today there are many types of forklifts on the market, these forklifts have different specifications and prices, making it difficult for shoppers to choose a product in many available types. This study has applied multi-criteria decision-making (MCDM) methods for forklift selection. Two MCDM methods having been used are the COCOSO (Combined Compromise Solution) method and PIV (Proximity Indexed Value) method. Two different methods having also been used to calculate the weights for the criteria are the ENTROPY method and MEREC (Method based on the Removal Effects of Criteria) method. The selection of the best type of forklift applies to the six available types. Six criteria having been used to describe each alternative are lifting height, maximum lifting height, minimum lifting height, fork length, fork width, and price. Each MCDM method will be used in combination with two weight methods. Thus, the ranking results of forklifts are shown in four different series of numbers. An amazing result has occurred that the best and worst forklifts have been consistently determined to be the same in all cases examined. This is the outstanding advantage of the COCOSO and PIV methods compared to other MCDM methods.
References
- Ulutaş, A., Stanujkić, D., Karabašević, D., Popović, G., Novaković, S. (2022). Pallet truck selection with MEREC and WISP-S methods. Strategic Management, 27 (4), 23–29. doi: https://doi.org/10.5937/straman2200013u
- Ortiz-Barrios, M., Cabarcas-Reyes, J., Ishizaka, A., Barbati, M., Jaramillo-Rueda, N., de Jesús Carrascal-Zambrano, G. (2020). A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry. Annals of Operations Research, 307 (1-2), 443–481. doi: https://doi.org/10.1007/s10479-020-03737-y
- Huskanović, E., Stević, Ž., Simić, S. (2023). Objective-Subjective CRITIC-MARCOS Model for Selection Forklift in Internal Transport Technology Processes. Mechatronics and Intelligent Transportation Systems, 2 (1), 20–31. doi: https://doi.org/10.56578/mits020103
- Fazlollahtabar, H., Smailbašić, A., Stević, Ž. (2019). FUCOM method in group decision-making: Selection of forklift in a warehouse. Decision Making: Applications in Management and Engineering, 2 (1), 49–65. doi: https://doi.org/10.31181/dmame1901065f
- Prusa, P., Jovcic, S., Nemec, V., Mrazek, P. (2018). Forklift truck selection using TOPSIS method. International Journal for Traffic and Transport Engineering, 8 (3), 390–398. doi: https://doi.org/10.7708/ijtte.2018.8(3).10
- Chakraborty, S., Saha, A. K. (2022). Selection of forklift unit for transport handling using integrated mcdm under neutrosophic environment. FACTA Universitatis. Series: Mechanical Engineering. Available at: http://casopisi.junis.ni.ac.rs/index.php/FUMechEng/article/view/10860/4654
- Atanasković, P., Gajić, V., Dadić, I., Nikoličić, S. (1970). Selection of Forklift Unit for Warehouse Operation by Applying Multi-Criteria Analysis. PROMET - Traffic&Transportation, 25 (4), 379–386. doi: https://doi.org/10.7307/ptt.v25i4.1338
- Agarski, B., Hadzistevic, M., Budak, I., Moraca, S., Vukelic, D. (2017). Comparison of approaches to weighting of multiple criteria for selecting equipment to optimize performance and safety. International Journal of Occupational Safety and Ergonomics, 25 (2), 228–240. doi: https://doi.org/10.1080/10803548.2017.1341126
- Ulutaş, A., Topal, A., Karabasevic, D., Balo, F. (2023). Selection of a Forklift for a Cargo Company with Fuzzy BWM and Fuzzy MCRAT Methods. Axioms, 12 (5), 467. doi: https://doi.org/10.3390/axioms12050467
- Huskanovic, E., Stevic, Z. (2022). Forklift selection using an integrated CRITIC-MARCOS model. 5th Logistics International Conference.Belgragde, 333–343. Available at: https://logic.sf.bg.ac.rs/wp-content/uploads/LOGIC_2022_ID_33.pdf
- Pamučar, D., Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42 (6), 3016–3028. doi: https://doi.org/10.1016/j.eswa.2014.11.057
- Dung, H. T., Do, D. T., Nguyen, V. T. (2022). Comparison of Multi-Criteria Decision Making Methods Using The Same Data Standardization Method. Strojnícky Časopis - Journal of Mechanical Engineering, 72 (2), 57–72. doi: https://doi.org/10.2478/scjme-2022-0016
- Do, T. (2021). The Combination of Taguchi – Entropy – WASPAS - PIV Methods for Multi-Criteria Decision Making when External Cylindrical Grinding of 65G Steel. Journal of Machine Engineering, 21 (4), 90–105. doi: https://doi.org/10.36897/jme/144260
- Trung, D. D. (2021). Application of EDAS, MARCOS, TOPSIS, MOORA and PIV Methods for Multi-Criteria Decision Making in Milling Process. Strojnícky Časopis - Journal of Mechanical Engineering, 71 (2), 69–84. doi: https://doi.org/10.2478/scjme-2021-0019
- Thinh, H. X., Mai, N. T., Giang, N. T., Khiem, V. V. (2023). Applying multi-criteria decision-making methods for cutting oil selection. Eastern-European Journal of Enterprise Technologies, 3 (1 (123)), 52–58. doi: https://doi.org/10.15587/1729-4061.2023.275717
- Son, N. H., Hieu, T. T. (2023). Selection of welding robot by multi-criteria decision-making method. Eastern-European Journal of Enterprise Technologies, 1 (3 (121)), 66–72. doi: https://doi.org/10.15587/1729-4061.2023.269026
- Trung, D. D., Thinh, H. X. (2021). A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study. Advances in Production Engineering & Management, 16 (4), 443–456. doi: https://doi.org/10.14743/apem2021.4.412
- Zhu, Y., Tian, D., Yan, F. (2020). Effectiveness of Entropy Weight Method in Decision-Making. Mathematical Problems in Engineering, 2020, 1–5. doi: https://doi.org/10.1155/2020/3564835
- Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2021). Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC). Symmetry, 13 (4), 525. doi: https://doi.org/10.3390/sym13040525
- Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57 (9), 2501–2519. doi: https://doi.org/10.1108/md-05-2017-0458
- Mufazzal, S., Muzakkir, S. M. (2018). A new multi-criterion decision making (MCDM) method based on proximity indexed value for minimizing rank reversals. Computers & Industrial Engineering, 119, 427–438. doi: https://doi.org/10.1016/j.cie.2018.03.045
- Gligorić, Z., Gligorić, M., Miljanović, I., Lutovac, S., Milutinović, A. (2023). Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm. Computer Modeling in Engineering & Sciences, 136 (1), 955–979. doi: https://doi.org/10.32604/cmes.2023.025021
- Salimian, S., Mousavi, S. M., Turskis, Z. (2023). Transportation Mode Selection for Organ Transplant Networks by a New Multi-Criteria Group Decision Model Under Interval-Valued Intuitionistic Fuzzy Uncertainty. Informatica, 34 (2), 337–355. doi: https://doi.org/10.15388/23-infor513
- Trung, D., Truong, N., Thinh, H. (2022). Combined PIPRECIA method and modified FUCA method for selection of lathe. Journal of Applied Engineering Science, 20 (4), 1355–1365. doi: https://doi.org/10.5937/jaes0-39335
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Tran Van Dua
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.