Selection of a Forklift for a Cargo Company with Fuzzy BWM and Fuzzy MCRAT Methods

Ulutaş, Alptekin; Topal, Ayşe; Karabašević, Darjan; Balo, Figen

doi:10.3390/axioms12050467

Cited by 11 publications

(9 citation statements)

References 57 publications

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“…This section applies the proposed hybrid fuzzy MEREC-G and fuzzy RATMI methods using the data from Ulutaş et al [48] to purchase a forklift that laborers can use in the warehouse. The following is an application of the three phases previously mentioned to rank the alternatives based on weighted criteria.…”

Section: Applications and Resultsmentioning

confidence: 99%

“…Step 3.5: In this step, the alternatives will be ranked twice. The first uses the fuzzy MCRAT [48], and the second uses fuzzy RAMS as a part of the proposed fuzzy RATMI. Ranking by fuzzy MCRAT uses the following sub-steps:…”

Section: Phase 3: Fuzzy Ratmi Methodsmentioning

confidence: 99%

“…However, fuzzy MCDM alternative ranking methods have been developed and applied to enable them to handle the uncertainty and ambiguity of decision-makers' subjective scoring inputs. Such methods are the fuzzy BWM [19][20][21][22][23][24][25][26], fuzzy additive ratio assessment (ARAS) [27][28][29], fuzzy measurement alternatives and ranking according to compromise solution (MARCOS) [30][31][32], fuzzy technique for order preference by similarity to ideal solution (TOPSIS) [24,33,34], fuzzy multi-attributive border approximation area comparison (MABAC) [35][36][37][38], fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) [39][40][41][42], fuzzy multi-attributive ideal-real comparative analysis (MAIRCA) [43][44][45][46][47], and, most recently, the fuzzy multiple criteria ranking by alternative trace (MCRAT) [48]. Several investigators applied the two components of MCDM in different fields [49][50][51][52][53][54][55][56][57][58][59][60]…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI

Makki,

Abdulaal

2023

Mathematics

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Multi-criteria decision-making (MCDM) assists in making judgments on complex problems by evaluating several alternatives based on conflicting criteria. Several MCDM methods have been introduced. However, real-world problems often involve uncertain and ambiguous decision-maker inputs. Therefore, fuzzy MCDM methods have emerged to handle this problem using fuzzy logic. Most recently, the method based on the removal effects of criteria using the geometric mean (MEREC-G) and ranking the alternatives based on the trace to median index (RATMI) were introduced. However, to date, there is no fuzzy extension of the two novel methods. This study introduces a new hybrid fuzzy MCDM approach combining fuzzy MEREC-G and fuzzy RATMI. The fuzzy MEREC-G can accept linguistic input terms from multiple decision-makers and generates consistent fuzzy weights. The fuzzy RATMI can rank alternatives according to their fuzzy performance scores on each criterion. The study provides the algorithms of both fuzzy MEREC-G and fuzzy RATMI and demonstrates their application in adopted real-world problems. Correlation and scenario analyses were performed to check the new approach’s validity and sensitivity. The new approach demonstrates high accuracy and consistency and is sufficiently sensitive to changes in the criteria weights, yet not too sensitive to produce inconsistent rankings.

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Section: Applications and Resultsmentioning

confidence: 99%

Section: Phase 3: Fuzzy Ratmi Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI

Makki,

Abdulaal

2023

Mathematics

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“…In this phase, a detailed financial analysis is carried out, which includes various parameters such as payback period, benefit-cost ratio, etc. A financial analysis can provide guidance on which forklift manufacturer to select [25,27]. However, given the requirements for sustainable material handling, it is clear that the forklift requires replacement by certain autonomous technologies.…”

Section: Practical Guidelines For Selecting Sustainable Materials Han...mentioning

confidence: 99%

Benefits and Challenges of Implementing Autonomous Technology for Sustainable Material Handling in Industrial Processes

Dabic-Miletic

2024

JII

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The transition from traditional production activities to a manufacturing-dominated economy has been a hallmark of industrial evolution, culminating in the advent of the fourth industrial revolution. This phase is characterized by the seamless integration of digital advancements across all sectors of global industry, heralding significant strides in meeting the evolving demands of markets and consumers. The concept of the smart factory stands at the forefront of this transformation, embedding sustainability, which is defined as economic viability, environmental stewardship, and social responsibility, into its core principles. This research focuses on the critical role of autonomous material handling technologies within these smart manufacturing environments, emphasizing their contribution to enhancing industrial productivity. The automation of material handling, propelled by the exigencies of reducing material damage, minimizing human intervention in repetitive tasks, and mitigating errors and service delays, is increasingly viewed as indispensable for achieving sustainable industrial operations. The employment of artificial intelligence (AI) in material handling not only offers substantial benefits in terms of operational efficiency and sustainability but also introduces specific challenges that must be navigated to align with the smart factory paradigm. By examining the integration of autonomous material handling solutions, traditionally epitomized by the utilization of forklifts in industrial settings, this study delineates the essential benchmarks for their implementation, ensuring compatibility with the overarching objectives of smart manufacturing systems. Through this lens, the paper articulates the dual imperative of aligning material handling technologies with environmental and social sustainability criteria, while also ensuring their economic feasibility.

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“…Thus, choosing the type of forklift will not ensure objectivity. In [9], the MCRAT method has been used to rank six different types of forklifts. The criteria having been used include price, lifting height, lowering speed, lifting speed, lifting capacity, range requirements, manufacturer reputation and spare parts availability.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Forklift selection by multi-criteria decision-making methods

Dua

2023

EEJET

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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.

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Selection of a Forklift for a Cargo Company with Fuzzy BWM and Fuzzy MCRAT Methods

Cited by 11 publications

References 57 publications

A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI

A Hybrid MCDM Approach Based on Fuzzy MEREC-G and Fuzzy RATMI

Benefits and Challenges of Implementing Autonomous Technology for Sustainable Material Handling in Industrial Processes

Forklift selection by multi-criteria decision-making methods

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