Graph Theory And Matrix Approach Research Articles

Reducing unnecessary handovers and improving ranking abnormality based on multi‐attribute decision making graph theory and matrix approach with Euclidean distance in heterogeneous wireless networks

SummaryNew mobile devices offer multiple network interfaces to allow the users to connect to the best available network. The heterogeneous networks can provide better internet connectivity to the users by means of vertical handover. The handover must be triggered at a suitable point of time to avoid mobility issues such as unnecessary handovers and handover ping‐pongs. The network selection during handover is usually done using classical multi‐attribute decision making (MADM) methods. However, ranking abnormality is one of the prominent issues of the classical MADM methods. To address these challenges, a graph theory and matrix approach (GTMA) with Euclidean distance is proposed for vertical handover in wireless networks. GTMA is used for the selection of the appropriate network and Euclidean distance is utilized for the handover triggering. The simulation results reveal that the proposed method has eliminated the ranking abnormality issue. This proposed technique without triggering has also reduced the number of handovers up to 75.61%, 85.71%, and 66.67% as compared to the traditional MADM methods such as AHP, GRA, and TOPSIS respectively. The use of Euclidean distance for handover triggering has further reduced the number of handovers of the proposed technique as well as traditional techniques for all the traffic types.

Valuation of inter-boundary inefficiencies accounting IoT based monitoring system in processed food supply chain

Nowadays, demand for processed food items is escalating towards the record consumption volume, which resulted in the surging of the Food Supply Chain (FSCs) network. But, the flow of the commodities through the various channels of the FSC is hampered by the various inefficiencies, which persist due to a lack of monitoring. This results in the widening of the gap between the supply and demand patterns allied with it. To tackle the same, and cater to the upwelling shares of the consumer demand, the dynamics of the Food Supply Chain Performance System (FSCPS) need to be tuned with the avenues of Industry 4.0 practices. Presented work clusters the various attributes of the inefficiencies, which hampers the processed FSCs dynamics and maintenance-related activities, elaborated by their sub-attributes based upon their events of occurrences. A model comprising the various attributes and sub-attributes of inefficiencies constrained outside the organizational boundaries of a firm’s FSC is rendered in this study. For effective handling of the mutual interdependencies persisting between the attributes, the methodology of the Graph Theory and Matrix Approach (GTMA) is exercised for the analysis of the developed model. Outcomes of the presented work felicitate the managers of industries, its allied corporates and numerous stakeholders of the FSC to ground a robust decisional framework, governing policies and managing the process permutations.

A strategic decision-making framework for sustainable reverse operations

Several factors, such as rapid industrial development, rising population, growing waste disposal, and exponential depletion of natural resources, have become a global challenge and call for a multifaceted approach to environmental protection. Rising consumers' awareness of environmental issues and the evolving ecological legislation puts pressure on businesses to adopt green practices in product design, manufacturing, distribution, and end-of-life disposition. Looking at these challenges, reverse logistics (RL) also known as reverse operations has become the most investigated theme in Supply Chain Management (SCM). Incorporating reverse logistics into the supply chain is not a simple task. Outsourcing reverse operations to the third-party reverse logistics service provider (3PRLSP) is an important strategic decision by many companies. This helps them to achieve a competitive advantage by reducing costs and improving quality processes and services. To this aim, this paper proposes a novel hybrid framework for selecting a 3PRLSP for the electronic industry. The first stage includes the preliminary screening of 3PRLSPs based on the method of effectiveness and compliance (E&C). In the second phase, graph theory and matrix approach (GTMA) is employed to choose the best 3PRLSP for outsourcing the reverse operations. The application of the proposed method is validated through a case-study based approach with reference to the Indian consumer electronic company. The data for the study was collected from experienced experts in senior managerial positions in the industry. The study findings revealed that the three dimensions of sustainability- economic, environmental and social, are vital in selecting 3PRLSP.

Interval-valued intuitionistic fuzzy digraph-matrix approach with PERMAN algorithm for measuring COVID-19 impact on perishable food supply chain.

The outbreak of COVID-19 has prompted a substantial shrinkage in various businesses worldwide, the perishable food sector being one of the worst hits. Henceforth, this manuscript intends to analyse the impact of COVID-19 on perishable food supply chains (PFSCs) of developed and developing countries. For this, the study presents the analysis in two steps. In the first step, the study illuminates the particular factors that frame unique sorts of supply chain (SC) disturbances in PFSC. Secondly, the study proposes a unique interval-valued intuitionistic fuzzy set (IVIFS)-based graph theory and matrix approach (GTMA) to analyse the COVID-19 impact index value. In addition to this, the PERMAN algorithm is used to calculate the permanent function. The study has revealed that developing nations should focus more on their technological and infrastructural factors to improve the condition of PFSC during the pandemic. This study’s results can be deployed by decision-makers to forestall the operative and long-haul consequences of COVID-19, or any other disruptions to the PFSC, and make plans to overcome the impact. The significance of this manuscript is that the prominent factors degrading the performance of PFSC amidst the pandemic have been highlighted, with their respective impact on developed and developing nations compared. Moreover, a neoteric comprehensive integration of IVIFS-GTMA technique along with the PERMAN algorithm has been utilised in this manuscript. This particular study is inimitable as it supplements existing literature by providing analytical support to the relationship among various factors impacting the PFSC amidst the pandemic.

OPTIMIZATION OF DIESEL ENGINE PERFORMANCE AND EMISSION CHARACTERISTICS EMPLOYING HYBRID TAGUCHI-GTMA-UTILITY TECHNIQUE

With the advent of employing bio-fuels along with the diesel in compression ignition engines the study of performance and emission characteristics have occupied the prominence, owing to diversified multi responses. As the limited information is available about the application of Taguchi based GTMA process to maximize the overall performance and emission characteristics of diesel engine, in the present work the investigation was carried out to maximize the overall utility by employing the Taguchi based GTMA process. By following the user preference rating, weights for the response characteristics namely brake thermal efficiency, brake specific fuel consumption, carbon monoxide and oxides of nitrogen were calculated using graph theory and matrix approach (GTMA). The parameter hydrogen induction played a major role to an extent of 78.62% while Injection opening pressure playing a minor role with a contribution of 7.06%. The optimal parameters condition was at mid-level of the governing parameters namely IOP, CR and volume of hydrogen inducted. The predicted results were within 95% of confidence interval of the optimal values. Therefore, the hydrogen inductance into the cylinder not only improving the performance but also minimizing the emission characteristics.

Uncovering interrelationships between barriers to unmanned aerial vehicles in humanitarian logistics

Recent disasters, such as the ongoing COVID-19 pandemic, have sparked an interest in new applications for unmanned aerial vehicles (UAVs) in humanitarian aid. Nevertheless, there are still many divisive changes that need to be made in order to implement UAVs into a country’s humanitarian sector successfully. Hence, this paper aims to analyze the various barriers hindering the implementation of UAVs in humanitarian logistics for both developed and developing nations. To accomplish this, the study is presented in three steps. First, previous literature and opinions from experts are analyzed to illuminate particular factors that hinder UAV implementation. Next, we propose an interval-valued intuitionistic fuzzy set (IVIFS) based graph theory and matrix approach (GTMA) to calculate a drone implementation hindrance index (DIHI). The GTMA method used in this paper utilizes the PERMAN algorithm to calculate the permanent function. Finally, the DIHI values are plotted and analyzed to compare the readiness of drone implementation between developed and developing economies. A sensitivity analysis is then performed to provide validity to the results obtained. The study has revealed that both types of countries must first improve their inadequate government regulations regarding humanitarian UAVs. Developing countries must also focus on enhancing the technological awareness of their population. The results of this study can be used by policymakers and practitioners to smoothly implement UAVs in their country's humanitarian sector. The general index defined in this paper can also be calculated for specific countries using the steps mentioned in the manuscript.

Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry

Helical milling is one of the high-performance and high-quality hole manufacturing activities with strong prospects for the automotive and aerospace industries. Literature suggests chip geometry plays a significant role in optimizing machining operations. In the present study, a mechanistic approach is used to estimate the chip geometry, cutting force and power/energy consumption concerning the tool rotation angle. Experiments are conducted at different levels of spindle rotational speed, cutter orbital speed and axial depth of cuts using 8 and 10 mm diameter mill cutters. Experimental results for cutting speed in X, Y and Z directions are measured. A hybrid approach, which combines the Taguchi method and Graph theory and matrix approach (GTMA) technique is used and optimized process parameters. The highest aggregate utility process parameters are met by 2000 rpm spindle speed, 50 rpm orbital speed and 0.2 mm axial cutting depth during helical milling of AISI D2 steel. FEM simulation is used for predicting the chip thickness, cutting forces and power consumption and also validated the optimization.

A decision support model for selecting unmanned aerial vehicle for medical supplies: context of COVID-19 pandemic

PurposeIn recent times, due to rapid urbanization and the expansion of the E-commerce industry, drone delivery has become a point of interest for many researchers and industry practitioners. Several factors are directly or indirectly responsible for adopting drone delivery, such as customer expectations, delivery urgency and flexibility to name a few. As the traditional mode of delivery has some potential drawbacks to deliver medical supplies in both rural and urban settings, unmanned aerial vehicles can be considered as an alternative to overcome the difficulties. For this reason, drones are incorporated in the healthcare supply chain to transport lifesaving essential medicine or blood within a very short time. However, since there are numerous types of drones with varying characteristics such as flight distance, payload-carrying capacity, battery power, etc., selecting an optimal drone for a particular scenario becomes a major challenge for the decision-makers. To fill this void, a decision support model has been developed to select an optimal drone for two specific scenarios related to medical supplies delivery.Design/methodology/approachThe authors proposed a methodology that incorporates graph theory and matrix approach (GTMA) to select an optimal drone for two specific scenarios related to medical supplies delivery at (1) urban areas and (2) rural/remote areas based on a set of criteria and sub-criteria critical for successful drone implementation.FindingsThe findings of this study indicate that drones equipped with payload handling capacity and package handling flexibility get more preference in urban region scenarios. In contrast, drones with longer flight distances are prioritized most often for disaster case scenarios where the road communication system is either destroyed or inaccessible.Research limitations/implicationsThe methodology formulated in this paper has implications in both academic and industrial settings. This study addresses critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria and sub-criteria rather than considering a fleet of drones is always at one's disposal.Practical implicationsThis research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.Social implicationsThe proposed methodology incorporates GTMA to assist decision-makers in order to appropriately choose a particular drone based on its characteristics crucial for that scenario.Originality/valueThis research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

Generalized fuzzy number and graph theory matrix approach in fuzzy decision making of smartphone selection

A number of studies have proposed a method of ranking a smartphone due to the fact that newly smartphones in the market are offering more features which could give more benefit to the user and thus become increasingly important as a tool in helping them to make everyday decisions. But most of the studies have exhibited shortcoming associated to level of confidence of decision makers’ in giving a judgement, which significantly influences final ranking result. This study proposes Graph Theory and Matrix Approach (GTMA) on ranking smartphone alternatives that ensures consideration of uncertainty and confidence level upon their judgement towards smartphone selection. A Generalized Triangular Fuzzy Number (GTFN) is used in the calculation of interrelation matrix which leads to give more meaningful value of importance weights of the attributes. Selection index is then calculated to rank the smartphone through fuzzy determinant. A numerical example is provided to illustrate the proposed approach whereby five well-known smartphones brand are considered which are apple, Samsung, Huawei, OPPO and Asus. The result shows that Huawei is the most preferred brand followed by OPPO and Apple in selecting the best smartphone.

Analysis on sustainable manufacturing criteria of automotive industry

In this paper, criteria within the most significant domain of manufacturing in automotive industry in Malaysia is analysed and prioritized. This paper aims to propose a multi criteria decision making (MCDM) procedure using concept of fuzzy theory, graph theory and Laplacian matrix approach which is embedded into Graph Theory and Matrix approach (GTMA). The manufacturing domains are ranked using Laplacian energy while the criteria within the most significant domain is prioritized using method of graph drawing whereby the criteria’s is ranked based on the average distance among other criteria in Cartesian coordinate system. The result indicates that cost, quality and service in economic domain are among significant criteria’s that practitioners should give an attention in developing a quality sustainable manufacturing framework so that the industry could sustain for a longer period of time.

Graph Theory and Matrix Approach (GTMA) Model for the Selection of the Femoral-Component of Total Knee Joint Replacement

Total Knee Replacement (TKR) is the increasing trend now a day, in revision surgery which is associated with aseptic loosening, which is a challenging research for the TKR component. The selection of optimal material loosening can be controlled at some limits. This paper is going to consider the best material selected among a number of alternative materials for the femoral component (FC) by using Graph Theory. Here GTMA process used for optimization of material and a systematic technique introduced through sensitivity analysis to find out the more reliable result. Obtained ranking suggests the use of optimized material over the other existing material. By following GTMA Co_Cr-alloys (wrought-Co-Ni-CrMo) and Co_Cr-alloys (cast-able-Co-Cr-Mo)are on the 1st and 2nd position respectively.

Identification and testing of barriers to sustainable manufacturing in the automobile industry: a focus on Indian MSMEs

PurposeThe purpose of the study is two-fold. First, to find out the different barriers that prevent the implementation of sustainable manufacturing practices in the case of Micro, Small and Medium Enterprises (MSMEs). Second, quantifying the relative intensity of these barriers to understand the importance and dependence power of the observed variables.Design/methodology/approachPrimary data were collected via structured questionnaires from 150 Indian MSMEs working in the automobile industry. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was performed. Finally, barriers are ranked using graph theory and matrix approach (GTMA), considering the inheritance and interaction among the observed variables.FindingsThere are a total of 22 barriers to “sustainable manufacturing”. EFA and CFA models confirmed four different categories of barriers. In order of importance, they are ranked as – production and operations related; organization related; collaboration related; and government rules and regulations.Practical implicationsThe findings show that there are multiple barriers to sustainable manufacturing. The barriers are categorized into four major categories, and their ranking provides an opportunity for prioritization from both policy and managerial perspectives. The barriers can be overcome through both policy interventions as well as through best practice sharing, benchmarking and organizational-wide initiatives.Originality/valueThe study is among the first studies that provide valuables insights on what are the 22 different barriers to sustainable manufacturing and its relevance to the MSMEs working in the automobile industry. The study would provide further opportunities for similar studies in different sectors.

Integration of AHP and GTMA to Make a Reliable Decision in Complex Decision-Making Problems: Application of the Logistics Provider Selection Problem as a Case Study

When solving a Multi-Criteria Decision-Making problem of any degree of complexity, many researchers rely on the analytic hierarchy process (AHP). To consider mutual connections between criteria and clusters at the same level and not only the hierarchical structure between criteria and subcriteria, researchers often upgrade from AHP to the Analytic Network Process (ANP), which also examines the interdependency of criteria. However, the ANP method requires a large number of pairwise comparisons. In the case of a complex decision-making problem, the authors of this paper suggest upgrading the AHP method with the graph theory and matrix approach (GTMA) for several reasons: (1) The new method is based on digraphs and permanent value computation, which does not require a hypothesis about interdependency; (2) in case of similar alternatives, the distinguishable coefficient of the new method is higher than those computed for AHP and ANP; (3) the new method allows decision makers to rank comparable alternatives and to combine structurally similar methods without increasing the number of comparisons and the understanding of the results. The developed method (AH-GTMA) is validated by a numerical example of a complex decision-making problem based on a symmetrical set of similar alternatives, a third party logistic provider (3PLP) selection problem.

An Integrated Smartphone and Tariff Plan Selection for Taxi Service Operators: MCDM and RStudio Approach

This paper aims to suggest a multi-criteria decision making (MCDM) approach in the business-to-business context in order to evaluate the smartphone options and tariff plans offered by mobile service providers in respect to the taxi service operators’ preference order. With the expert questionnaire filled by decision makers (DMs) of taxi service operating firms and real data collected from heterogeneous data sources, three MCDM techniques are utilized in the selection process: an analytic hierarchy process is utilized to set the relative weights of the smartphone and tariff plan evaluation criteria. Furthermore, the technique for order preference by similarity to ideal solutions and graph theory and matrix approach (GTMA) are applied to select an ideal smartphone and its relevant tariff plan for taxi service operators. The GTMA weights are obtained by the proposed self-written algorithms in RStudio software. The results show that the most ideal smartphone for taxi service operators is Lenovo A2016 (LTE) offered by Azercell mobile service provider. In addition, the most suitable tariff plan along with the smartphone is “Optimist Talk” with 3000 on-net and 300 off-net minutes, 300 SMS, and the 3000-MB Internet, which costs only 29 AZN per month. This paper fills the gap in the literature that no former studies combined above-mentioned three MCDM techniques to select an ideal smartphone as well as tariff plan, which are offered by mobile service providers. In addition, using three techniques, particularly the R script implementing the dynamic-programming concept to calculate the assessed index scores for GTMA, significantly contribute to DMs in the B2B context to find an ideal solution not only in the mobile service but also in other domains.

A hybrid approach to multi response optimization of micro milling process parameters using Taguchi method based graph theory and matrix approach (GTMA) and utility concept

Nowadays, it is required to produce micro products with high dimensional accuracy to use them in different applications like aerospace, electronic and optics. The objective of this study is to investigate influence of process parameters on surface roughness (Ra and Rq), tool wear and cutter vibration in micro milling of AISI304 stainless steel. According to orthogonal array of L27, twenty-seven experiments were conducted on the workpiece with carbide end mill cutter at different levels of spindle speeds, feeds and depth of cuts. A hybrid approach of Taguchi method based graph theory and matrix approach (GTMA) and utility concept was used for multi response optimization of process parameters. The GTMA was used to calculate weightage of four responses as per user’s opinion or preference. The utility concept was used to calculate utility value of four responses using preference scale. Mean utility values of responses are analyzed with Taguchi method and analysis of variance. The optimum process parameters for the minimization responses were found to be 6000 rpm of spindle speed, 95 µm/teeth of feed and 50 µm of depth of cut. The predicted responses at optimal process parameters are Ra = 0.534 µm, VB = 70.861 µm, Amp = 54.395 µm and Rq = 0.894 µm. A confirmation test was also carried out to verify the results.

Assignment of weightage to machining characteristics to improve overall performance of machining using GTMA and utility concept

In an automated manufacturing system, performance of machining is an important characteristic that affects the production cost especially in machining processes like milling and boring. Boring is one of critical machining processes, and therefore, it is very difficult to determine overall performance of the process. In the present work, an attempt was made to maximize overall performance of the process in order to reduce reworking and production cost. Three different performance characteristics like surface roughness, tool wear and root mean square of workpiece vibration velocity are considered to determine overall performance for boring of AISI 1040 steel with carbide tool inserts. According to User's Preference Rating, weights for the three performance characteristics are calculated using graph theory and matrix approach (GTMA). Overall performance or utility value of the machining process is calculated using utility concept. A response surface methodology (RSM) is used to optimize the process parameters for maximization of performance of the process. Weights of surface roughness, tool wear and root mean square of workpiece vibration velocity are calculated as 0.489, 0.367 and 0.184 respectively. Optimum process parameters were found to be 0.4mm of nose radius, 170m/min of cutting speed and 0.1358mm/rev of feed rate.

Evaluation and benchmarking of lean manufacturing system environment: A graph theoretic approach

Article history: Received April 20, 2015 Received in revised format October 10, 2015 Accepted October 15 2015 Available online October 16 2015 Manufacturing industries are consistently working on improving their operational performance to remain competitive in the market. LM is a well-recognized approach for improving the overall performance. It contains several elements covered under a few lean attributes. This paper presents the application of Graph Theory and Matrix Approach (GTMA) for the identification of relative importance of different lean attributes in a lean environment using qualitative and quantitative factors. The Lean Manufacturing Attributes (LMA’s), affecting the overall LM environment, of a manufacturing industry were identified and analyzed for the implications on the managerial decisions. .In this proposed study, The GTMA approach is applied to prioritize the LMA’s based on their relative importance. Growing Science Ltd. All rights reserved. 6 © 201

Modeling and analysis of FMS performance variables by ISM, SEM and GTMA approach

The purpose of this paper is to analyze the performance variables of flexible manufacturing system (FMS). This study was performed by different approaches viz. interpretive structural modelling (ISM); Structural equation modelling (SEM); Graph Theory and Matrix Approach (GTMA) and a cross-sectional survey within manufacturing firms in India. ISM has been used to develop a hierarchical structure of performance variables, and to find the driving and the dependence power of the variables. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are powerful statistical techniques. By performing EFA, factor structure is placed. Whereas CFA verified the factor structure of a set of observed variables. CFA is carried by SEM statistical technique. EFA is applied to extract the factors in FMS by The Statistical Package for Social Sciences (SPSS 20) software and confirming these factors by CFA through Analysis of Moment Structures (AMOS 20) software. The fifteen performance variables are identified through literature, and three factors extracted, which involves the performance of FMS. The three factors are Quality, Productivity and Flexibility. SEM using AMOS 20 was used to perform the first order three factor structure. GTMA is a Multiple Attribute Decision Making (MADM) Methodology used to find intensity/quantification of performance variables in an organization. The FMS Performance Index has purposed to intensify the factors which affect FMS.

Evaluating the intensity of variables affecting flexibility in FMS by graph theory and matrix approach

The purpose of this paper is to investigate the intensity of variables of the flexible manufacturing system (FMS) which affect flexibility in FMS. The study was performed by conducting a cross–sectional survey within manufacturing firms in India through exploratory factor analysis (EFA) and graph theory and matrix approach (GTMA). By performing EFA, factor structure is identified whereas GTMA quantified the factor structure of a set of observed variables. GTMA is a multiple attribute decision making (MADM) methodology used to find the intensity of variables in an organisation. In this paper, EFA is applied to extract the factors in FMS by The Statistical Package for Social Sciences (SPSS 20) software and evaluation of intensity of variables affecting flexibility in FMS by GTMA. Fifteen variables are identified through literature, and four factors extracted, which involves the flexibility of FMS in production flexibility, machine flexibility, product flexibility, and volume flexibility.

Selection of Locations of Collection Centers for Reverse Logistics Using GTMA

The application of reverse logistics is gaining attention with the pressure from environmental and social necessities. An efficient management of return of products is a taxing task because of uncertainty involved. To reduce this, the returned products are collected into collection sites. Hence, for an efficient reverse supply chain, the location of collection sites must be appropriate in order to make it profitable for the organization. In this paper we discuss the Graph Theory and Matrix Approach (GTMA) to find the location of collection sites. A case study has been presented to illustrate the method.