Garuda - Garba Rujukan Digital

Integration of Fuzzy 0/1 Knapsack Dynamic Programming and PROMETHEE Method for Vehicle Exhaust Emission Parametric Optimization and Selection in the Packing Industry Agada, Alexander Iwodi; Rajan, John; Jose, Swaminathan; Oke, Sunday Ayoola; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 6 No. 2 (2024)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v6i2.7689

Packaging industries fabricate and transport products in wrapped, sealed, and cushioned containers and boxes on roads, often through fossil-fuelled vehicles that emit carbons. Thus, decarbonization and net zero emission drive are compelling for these vehicles. This paper proposes a robust green logistics interaction model for monitoring and reducing exhaust pipe emissions in an uncertain environment. It uses a hybrid method known as fuzzy-0/1-KDP-PROMETHEE (Fuzzy-0/1 Knapsack dynamic programming-Preference Ranking Organization Method for Enrichment Evaluation) approach to concurrently reduce uncertainty, optimize the capacity of the knapsack and establish the preferred option among the parameters of green logistic. Both PROMETHEE I and II were introduced and tested using logistics data from an Indian environment based on secondary data. The method works by first reducing the effect of uncertainty on the model outcomes. This was achieved by establishing the output space as the fuzzy state, creating fuzzy rules, and mapping degrees to rules. Then, the degrees are used to maximize, ensuring that the weighted sum is not greater than the capacity of the Knapsack. The outcome is then regarded as the element of the green logistics exhaust emission process. The results obtained from the analysis, using the replacement of fuzzy expert (triangular) with fuzzy extent (trapezoidal), fuzzy geometric mean (triangular), and fuzzy geometric mean (trapezoidal) reveal that the fuzzy-0/1-KDP-PROMETHEE method adequately represents the score obtained using the data set from the exhaust emissions.

Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory Agada, Alexander Iwodi; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 2 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i2.7740

Precise monitoring of vehicle emissions in green logistics, focusing on the contributions of vehicles from packing industries, is crucial for many issues. It helps to understand the total emissions and gain insights into the mechanism of vehicle-associated environmental concerns. Notwithstanding, a key issue when monitoring vehicle emissions is the effective discrimination problem for different patterns generated from the parameters. Data from the packing industry are available from distribution networks but its pattern cannot be discriminated. Given this background, this article presents a new method of the orthogonal array-based rough set to discern patterns of the parametric behaviors to monitor emissions from vehicle exhausts in the packing industry. The proposed method is based on an Indian logistics network and delivery system data, which was obtained from previous work in the literature. By setting controls on the parameters of the packing industry which includes revenue obtained, packing units sold, growth rate, carbon-dioxide equivalent, materials utilized, and quantity consumed, the method was able to discern the patterns of the parametric behavior. The orthogonal arrays, which are developed, form factors (parameters) and levels to ascertain a balanced and uniform analysis of the various groups of options. Indiscernibility and approximation concepts of fuzzy sets are then applied to arrive at the outcome. Unlike previous studies, this study eliminates the need for tracking data, assumptions, and external information to establish the set membership. However, it utilizes the available information within the data. The rough set analysis indicates that there are no discernable patterns or rules that distinguish between "Yes" and "No" decisions. The method of rough set illustrated in this work shows the feasibility of the approach in the Indian packing industry. The method is useful for the logistics manager and government agencies responsible for the control of vehicle-generated greenhouse emissions.

Green Supplier Evaluation and Selection in the Manufacturing Industry Using the Taguchi-VIKOR Methods Adedeji, Wasiu Oyediran; Olowu, Joseph Kolawole; Adeniran, Mofoluwaso Kehinde; Oyelami, Seun; Adeboye, Busayo; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oke, Sunday Ayoola
International Journal of Industrial Engineering and Engineering Management Vol. 7 No. 1 (2025)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v7i1.7778

This paper proposes three methods for the joint optimization and selection of parameters in controlling the exhaust emission from logistics and packing industries, using the Taguchi-VIKOR, Taguchi-Pareto-VIKOR, and Taguchi-ABC-VIKOR methods. From the delta values of the Taguchi method, parameters F, E, A, B, C, and D were placed 1st, 2nd, 3rd, 4th, 5th, and 6th with delta values of 59.0066, 7.5263, 7.5261, 0.1150, 0.1113 and 0.1107, respectively. The delta ratio, delta variability, mean delta value and median delta value are 58.8959, 12.3993, and 3.8206, respectively. Furthermore, the optimal parametric setting is A1B1C1D1E1F1, which means 52 million dollars for revenue, 127 billion packing units, 0.77 optimal growth rate, 1.5 units of materials, 5581 kilotons of quantity consumed and 1 unit of carbon dioxide equivalent of packing materials. The methods are the cornerstone for evaluating the high-performing packing factor associated with greenhouse gas emissions and concurrently obtaining optimized values for packing enterprises to reduce emissions. Besides, and differently from earlier studies, methods such as Pareto, ABC, and VIKOR differentiate the alternative coupled Taguchi methods proposed in the literature. In addition, the following novel elements of the Taguchi method are introduced: Delta ratio, delta variability, mean delta value, delta/HOPV, delta/LOPV, and delta/AOPV. The results suggest that the developed methods adequately represent the optimized values and ranks obtained using the field data set from literature.

Green Supplier Evaluation and Selection in the Manufacturing Industry Using the Taguchi-VIKOR Methods Adedeji, Wasiu Oyediran; Olowu, Joseph Kolawole; Adeniran, Mofoluwaso Kehinde; Oyelami, Seun; Adeboye, Busayo; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oke, Sunday Ayoola
International Journal of Industrial Engineering and Engineering Management Vol. 7 No. 1 (2025)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v7i1.7778

This paper proposes three methods for the joint optimization and selection of parameters in controlling the exhaust emission from logistics and packing industries, using the Taguchi-VIKOR, Taguchi-Pareto-VIKOR, and Taguchi-ABC-VIKOR methods. From the delta values of the Taguchi method, parameters F, E, A, B, C, and D were placed 1st, 2nd, 3rd, 4th, 5th, and 6th with delta values of 59.0066, 7.5263, 7.5261, 0.1150, 0.1113 and 0.1107, respectively. The delta ratio, delta variability, mean delta value and median delta value are 58.8959, 12.3993, and 3.8206, respectively. Furthermore, the optimal parametric setting is A1B1C1D1E1F1, which means 52 million dollars for revenue, 127 billion packing units, 0.77 optimal growth rate, 1.5 units of materials, 5581 kilotons of quantity consumed and 1 unit of carbon dioxide equivalent of packing materials. The methods are the cornerstone for evaluating the high-performing packing factor associated with greenhouse gas emissions and concurrently obtaining optimized values for packing enterprises to reduce emissions. Besides, and differently from earlier studies, methods such as Pareto, ABC, and VIKOR differentiate the alternative coupled Taguchi methods proposed in the literature. In addition, the following novel elements of the Taguchi method are introduced: Delta ratio, delta variability, mean delta value, delta/HOPV, delta/LOPV, and delta/AOPV. The results suggest that the developed methods adequately represent the optimized values and ranks obtained using the field data set from literature.

Integration of Fuzzy 0/1 Knapsack Dynamic Programming and PROMETHEE Method for Vehicle Exhaust Emission Parametric Optimization and Selection in the Packing Industry Agada, Alexander Iwodi; Rajan, John; Jose, Swaminathan; Oke, Sunday Ayoola; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 6 No. 2 (2024)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v6i2.7689

Packaging industries fabricate and transport products in wrapped, sealed, and cushioned containers and boxes on roads, often through fossil-fuelled vehicles that emit carbons. Thus, decarbonization and net zero emission drive are compelling for these vehicles. This paper proposes a robust green logistics interaction model for monitoring and reducing exhaust pipe emissions in an uncertain environment. It uses a hybrid method known as fuzzy-0/1-KDP-PROMETHEE (Fuzzy-0/1 Knapsack dynamic programming-Preference Ranking Organization Method for Enrichment Evaluation) approach to concurrently reduce uncertainty, optimize the capacity of the knapsack and establish the preferred option among the parameters of green logistic. Both PROMETHEE I and II were introduced and tested using logistics data from an Indian environment based on secondary data. The method works by first reducing the effect of uncertainty on the model outcomes. This was achieved by establishing the output space as the fuzzy state, creating fuzzy rules, and mapping degrees to rules. Then, the degrees are used to maximize, ensuring that the weighted sum is not greater than the capacity of the Knapsack. The outcome is then regarded as the element of the green logistics exhaust emission process. The results obtained from the analysis, using the replacement of fuzzy expert (triangular) with fuzzy extent (trapezoidal), fuzzy geometric mean (triangular), and fuzzy geometric mean (trapezoidal) reveal that the fuzzy-0/1-KDP-PROMETHEE method adequately represents the score obtained using the data set from the exhaust emissions.

Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory Agada, Alexander Iwodi; Oke, Sunday Ayoola; Rajan, John; Jose, Swaminathan; Benrajesh, Pandiaraj; Oyetunji, Elkanah Olaosebikan; Adedeji, Kasali Aderinmoye
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 2 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i2.7740

Precise monitoring of vehicle emissions in green logistics, focusing on the contributions of vehicles from packing industries, is crucial for many issues. It helps to understand the total emissions and gain insights into the mechanism of vehicle-associated environmental concerns. Notwithstanding, a key issue when monitoring vehicle emissions is the effective discrimination problem for different patterns generated from the parameters. Data from the packing industry are available from distribution networks but its pattern cannot be discriminated. Given this background, this article presents a new method of the orthogonal array-based rough set to discern patterns of the parametric behaviors to monitor emissions from vehicle exhausts in the packing industry. The proposed method is based on an Indian logistics network and delivery system data, which was obtained from previous work in the literature. By setting controls on the parameters of the packing industry which includes revenue obtained, packing units sold, growth rate, carbon-dioxide equivalent, materials utilized, and quantity consumed, the method was able to discern the patterns of the parametric behavior. The orthogonal arrays, which are developed, form factors (parameters) and levels to ascertain a balanced and uniform analysis of the various groups of options. Indiscernibility and approximation concepts of fuzzy sets are then applied to arrive at the outcome. Unlike previous studies, this study eliminates the need for tracking data, assumptions, and external information to establish the set membership. However, it utilizes the available information within the data. The rough set analysis indicates that there are no discernable patterns or rules that distinguish between "Yes" and "No" decisions. The method of rough set illustrated in this work shows the feasibility of the approach in the Indian packing industry. The method is useful for the logistics manager and government agencies responsible for the control of vehicle-generated greenhouse emissions.

Title

Found 6 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 6 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 6 Documents
Search