AN INTEGRATED DECISION-MAKING MODEL FOR EFFICIENCY ANALYSIS OF THE FORKLIFTS IN WAREHOUSING SYSTEMS

Eldina Mahmutagić, Željko Stević, Zdravko Nunić, Prasenjit Chatterjee, Ilija Tanackov

DOI Number
10.22190/FUME210416052M
First page
537
Last page
553

Abstract


In the logistics world, special attention should be given to warehousing systems, cost rationalization, and improvement of all the factors that affect efficiency and contribute to smooth functioning of logistics subsystems. In real time industrial practice, the issue of evaluating and selecting the most appropriate forklift involves a complex decision-making problem that should be formulated through an efficient analytical model. The forklifts efficiency plays a very important role in the company. The forklifts are being used on a daily basis and no logistical processes could be done without them. Therefore, it has been decided to determine their efficiency, which will contribute to the optimization of the process in this logistics subsystem. This study puts forward an integrated forklift selection model using Data Envelopment Analysis (DEA), Full Consistency Method (FUCOM) and Measurement Alternatives and Ranking According to the Compromise Solution (MARCOS) methods. Five input parameters (regular servicing costs, fuel costs, exceptional servicing costs, total number of all minor accidents and damage caused by forklifts) and one output parameter (number of operating hours) were first identified to assess efficiency of eight forklifts in a warehousing system of the Natron-Hayat company using the DEA model. This step allows sorting of efficient forklifts which are subsequently evaluated and ranked using FUCOM and MARCOS methods. A sensitivity analysis is also performed in order to check reliability and accuracy of the results. The findings of this research clearly show that the proposed decision-making model can significantly contribute to all spheres of business applications.

Keywords

DEA, FUCOM, MARCOS, Warehouse, Forklifts

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References


Šporčić, M., Martinić, I., Landekić, M., Lovrić, M., 2008, Analiza o međivanja podataka kao metod aefikasnosti–mogućnosti primjene u šumarstvu, Časopis za teoriju i praksu šumarskoga inženjerstva, 29(1), pp. 51-59.

Charnes, A., Cooper, W.W., Rhodes, E., 1978, Measuring the efficiency of decision-making units, European Journal of Operational Research, 2(6), 429-444.

Cavaignac, L., Dumas, A., Petiot, R., 2020, Third-party logistics efficiency: an innovative two-stage DEA analysis of the French market, International Journal of Logistics Research and Applications, pp. 1-24.

Andrejić, M. M., 2013, Measuring efficiency in logistics, Vojnotehnički glasnik, 61(2), pp. 84-104.

Andrejic, M. M., Kilibarda, M.J., 2016, Measuring global logistics efficiency using PCA-DEA approach, Tehnika, 71(5), pp. 733-740.

Karande, A., Krishna, A., Jayasurya, R., Gopan, G., Gopinath, M. V., Kumar, S., Varaprasad, G., 2019, Performance Analysis of Storage Warehouses in a Food Grain Supply Chain using Data Envelopment Analysis, In2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), pp. 1-4.

Tian, N., Tang, S., Che, A., Wu, P., 2020, Measuring regional transport sustainability using super-efficiency SBM-DEA with weighting preference,Journal of Cleaner Production, 242, 118474.

Kilibarda, M., Andrejic, M., Popovic, V., 2017, Efficiency of logistics processes in customs procedures, In 3rd Logistics International Conference Serbia, pp. 45-51.

Amirteimoori, A., Khoshandam, L., 2011, A Data Envelopment Analysis Approach to Supply Chain Efficiency, Advances in Decision Sciences, 2011, 608324-1.

Ćiraković, L. S., Bojović, N. J., Milenković, M. S. 2014, Analiza efikasnosti autobuskog podsistema javnog transporta putnika u gradu Beogradu, korišćenjem DEA metode. Tehnika, 69(6), pp. 1032-1039.

Dožić, S., Babić, D. 2015, Efikasnost aviokompanija u Evropskoj uniji: primena AHP i DEA metoda, SYM-OP-IS 2015: XLII Simpozijum o operacionim istraživanjima pp. 512-515.

Krstić, M., Tadić, S., Zečević, S. 2020, Analiza efikasnosti evropskih kopnenih trimodalnih terminala, XLVII Simpozijum o operacionim istraživanjima pp. 231-236.

Blagojević, A., Stević, Ž., Marinković, D., Kasalica, S., Rajilić, S., 2020, A novel entropy-fuzzy PIPRECIA-DEA model for safety evaluation of railway traffic, Symmetry, 12(9), 1479.

Mitrović Simić, J., Stević, Ž., Zavadskas, E. K., Bogdanović, V., Subotić, M., Mardani, A., 2020, A Novel CRITIC-Fuzzy FUCOM-DEA-Fuzzy MARCOS Model for Safety Evaluation of Road Sections Based on Geometric Parameters of Road, Symmetry, 12(12), 2006.

Despić, D.R., Bojović, N.J., Kilibarda, M.J., Kapetanović, M.V., 2019, Assessment of efficiency of military transport units using the DEA and SFA method, Vojnotehnički glasnik, 67(1), pp. 68-92.

Lu, W., 2019, Port Logistics Efficiency Evaluation Based on DEA Model, International conference on Big Data Analytics for Cyber-Physical-Systems, pp. 461-467, Springer.

Pamučar, D. S., Savin, L. M., 2020, Multiple-criteria model for optimal off-road vehicle selection for passenger transportation: BWM-COPRAS model, Vojnotehnički glasnik, 68(1), pp. 28-64.

Pamučar, D., Stević, Ž., Sremac, S., 2018, A new model for determining weight coefficients of criteria in mcdm models: Full consistency method (fucom), Symmetry, 10(9), 393.

Durmić, E., Stević, Ž., Chatterjee, P., Vasiljević, M., Tomašević, M., 2020, Sustainable supplier selection using combined FUCOM–Rough SAW model, Reports in Mechanical Engineering, 1(1), pp. 34-43.

Zavadskas, E.K., Nunić, Z., Stjepanović, Ž., Prentkovskis, O., 2018, A novel rough range of value method (R-ROV) for selecting automatically guided vehicles (AGVs), Studies in Informatics and Control, 27(4), pp. 385-394.

Đalić, I., Stević, Ž., Erceg, Ž., Macura, P., Terzić, S., 2020, Selection of adistribution channel using the integrated FUCOM-MARCOS model, International Review, (3-4), pp. 91-107.

Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P., 2020, Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS), Computers & Industrial Engineering, 140, 106231.

Puška, A., Stević, Ž., Stojanović, I., Selection of Sustainable Suppliers Using the Fuzzy MARCOS Method, Current Chinese Science, 1(1), doi: 10.2174/2210298101999201109214028.

Ulutaş, A., Karabasevic, D., Popovic, G., Stanujkic, D., Nguyen, P. T., Karaköy, Ç., 2020, Development of a novel integrated CCSD-ITARA-MARCOS decision-making approach for stackers selection in a logistics system. Mathematics, 8(10), 1672.

Zavadskas, E. K., Turskis, Z., 2010, A new additive ratio assessment (ARAS) method in multicriteria decision‐making, Technological and Economic Development of Economy, 16(2), pp. 159-172.

Pamučar, D., Ćirović, G., 2015, The selection of transport and handling resources in logistics centres using Multi-Attributive Border Approximation area Comparison (MABAC), Expert systems with applications, 42(6), pp. 3016-3028.

Chakraborty, S., Ghosh, S., Sarker, B., Chakraborty, S., 2020, An integrated performance evaluation approach for the Indian international airports, Journal of Air Transport Management, 88, 101876.

Anggraeni, E.Y., Huda, M., Maseleno, A., Safar, J., Jasmi, K. A., Mohamed, A. K., Masrur, M., 2018, Poverty level grouping using SAW method, International Journal of Engineering and Technology, 7(27), pp. 218-224.

Zavadskas, E.K., Turskis, Z., Antucheviciene, J., Zakarevicius, A., 2012, Optimization of weighted aggregated sum product assessment, Elektronikairelektrotechnika, 122(6), pp. 3-6.

KeshavarzGhorabaee, M.,Zavadskas, E. K., Olfat, L., Turskis, Z., 2015, Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS),Informatica, 26(3), pp. 435-451.

Yazdani, M., Zarate, P., Zavadskas, E.K., Turskis, Z., 2019, A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems, Management Decision, 57(9), pp. 2501-2519.

Chen, P., 2019, Effects of normalization on the entropy-based TOPSIS method, Expert Systems with Applications, 136, pp. 33-41.

Adler, N., Yazhemsky, E. 2010,Improving discrimination in data envelopment analysis: PCA–DEA or variable reduction. European Journal of Operational Research, 202(1), pp. 273-284.




DOI: https://doi.org/10.22190/FUME210416052M

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ISSN: 2335-0164 (Online)

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