Distribution planning using capacitated clustering and vehicle routing problem

Rautela, Anubha; Sharma, S.K.; Bhardwaj, Prabhas

doi:10.1108/jamr-12-2018-0113

Cited by 10 publications

(6 citation statements)

References 31 publications

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“…Then in the second step, it clusters the data to the nearest center with the consideration to Euclidean distance from the cluster center to each data object (Na et al , 2010). For more details on the K -means algorithm, Morissette and Chartier (2013), Na et al (2010), Kapoor and Singhal (2017), Oyelade et al (2010) and Rautela et al (2019) may be considered.…”

Section: Methodsmentioning

confidence: 99%

Narrowing the barriers to Industry 4.0 practices through PCA-Fuzzy AHP-K means

Kumar

Suhaib

Asjad

2020

JAMR

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PurposeThe study aims to analyze the barriers in the adoption of Industry 4.0 (I4.0) practices in terms of prioritization, cluster formation and clustering of empirical responses, and then narrowing them with identification of the most influential barriers for further managerial implications in the adoption of I4.0 practices by developing an enhanced understanding of I4.0.Design/methodology/approachFor the survey-based empirical research, barriers to I.40 are synthesized from the review of relevant literature and further discussions with academician and industry persons. Three widely acclaimed statistical techniques, viz. principal component analysis (PCA), fuzzy analytical hierarchical process (fuzzy AHP) and K-means clustering are applied.FindingsThe novel integrated approach shows that lack of transparent cost-benefit analysis with clear comprehension about benefits is the major barrier for the adoption of I4.0, followed by “IT infrastructure,” “Missing standards,” “Lack of properly skilled manpower,” “Fitness of present machines/equipment in the new regime” and “Concern to data security” which are other prominent barriers in adoption of I4.0 practices. The availability of funds, transparent cost-benefit analysis and clear comprehension about benefits will motivate the business owners to adopt it, overcoming the other barriers.Research limitations/implicationsThe present study brings out the new fundamental insights from the barriers to I4.0. The new insights developed here will be helpful for managers and policymakers to understand the concept and barriers hindering its smooth implementation. The factors identified are the major thrust areas for a manager to focus on for the smooth implementation of I4.0 practices. The removal of these barriers will act as a booster in the way of implementing I4.0. Real-world testing of findings is not available yet, and this will be the new direction for further research.Practical implicationsThe new production paradigm is highly complex and evolving. The study will act as a handy tool for the implementing manager for what to push first and what to push later while implementing the I4.0 practices. It will also empower a manager to assess the implementation capabilities of the industry in advance.Originality/valuePCA, fuzzy AHP and K means are deployed for identifying the significant barriers to I4.0 first time. The paper is the result of the original conceptual work of integrating the three techniques in the domain of prioritizing and narrowing the barriers from 16 to 6.

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Section: Methodsmentioning

confidence: 99%

Narrowing the barriers to Industry 4.0 practices through PCA-Fuzzy AHP-K means

Kumar

Suhaib

Asjad

2020

JAMR

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“…The positive impact of economic clusters on the level of development of countries is based on several features that emerge for the financial entities participating in innovation clusters: uniqueness of the internal environment and infrastructure of the cluster; strengthening interconnections and relationships formed between participants; openness of information, trust between cluster subjects; changes in the company/cluster's overall intellectual capital; increasing the level of employee competence, changing management style and psychology, improving social security, building new communication networks; access to new technologies, R&D findings; joint scientific research aimed at further introduction into production; financing effectiveness; cost reduction (Rautela et al, 2019) , stable position in the market; positive impact on other economic entities in the region; positive experiences of the cluster and its participants that influence the reputation of the area and the country as a whole (Kookueva & Tsertseil, 2018) .…”

Section: Effect Of Clustering On Intellectual Capital On Competitive ...mentioning

confidence: 99%

The Influence of Resources on Competitive Advantage through Clustering in Printing Companies in JABODETABEK

Dance

2024

ijsh

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Flexible packaging is the most widely consumed packaging material in the Indonesian packaging industry, estimated to reach 43.8% by 2024. This research aims to present a conceptual framework and understanding for MSME printing companies in Jabodetabek to achieve competitive advantage through clustering using limited assets capacity, intellectual capital, and innovative capabilities based on a review of relevant literature and integrated through existing theory. The analysis results are based on 32 questionnaires collected from MSME printing companies in Jabodetabek. This research was tested using Structural Equation Modeling (SEM) to test the conceptual framework empirically. The research results show that capacity-constrained assets have a direct effect on clustering and do not affect competitive advantage but indirectly affect competitive advantage mediated by clustering. Intellectual capital does not directly influence competitive advantage and clustering, but indirectly influences competitive advantage mediated by clustering. Innovative capability has a direct effect on competitive advantage and clustering but indirectly has no effect on competitive advantage mediated by clustering. Clustering directly affects competitive advantage. Therefore, with the emergence of many new printing machines, ease of interaction with printers receiving print processing services, and the high level of utilization of business services from the internet, clustering can be implemented so that MSME printing companies in Jabodetabek can achieve competitive profits.

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“…e general transportation problem of automobiles is to make the total transportation distance the shortest or the transportation cost the lowest [14].…”

Section: Mathematical Model Of Vehicle Transportation Routementioning

confidence: 99%

Optimization of Vehicle Transportation Route Based on IoT

Wang

Jiang

et al. 2021

Mathematical Problems in Engineering

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With the rapid development of logistics industry, optimization of road transport has become a constraint that must be overcome in the development of related industries. In the IoT era, classic car routing solutions could not meet many different needs. The relevant research findings are endless but not suitable to reduce costs in logistics and distribution processes and meet the needs of customers. This paper researches on vehicle path optimization using IoT technology and intelligent algorithms. Firstly, the traditional GA is optimized, and its coding mode, fitness function, selection, crossover, and mutation operators are studied. The crossover probability was set to 0.6, and the mutation probability was set to 0.1; then, according to the improved GA, a vehicle route optimization model was created. Finally, simulations were conducted to optimize vehicle routes for some distribution centers and 15 customer sites, and the model’s validity was tested. Experimental data show that the improved genetic algorithm begins to converge in 100 generations with a running time of 37.265 s. We calculate the time sensitivity of the customer. An algorithmic model is then used to determine distribution plans based on product demand and time sensitivity. In addition, we compare distribution costs and customer satisfaction of algorithmic and randomized plans. The distribution cost and customer satisfaction of the algorithmic and random patterns were 498.09 yuan and 573.13 yuan and 140.45 and 131.35, respectively. This shows that the vehicle routing optimization model using IoT technology and an improved GA can reduce distribution costs and increase customer satisfaction.

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Distribution planning using capacitated clustering and vehicle routing problem

Cited by 10 publications

References 31 publications

Narrowing the barriers to Industry 4.0 practices through PCA-Fuzzy AHP-K means

Narrowing the barriers to Industry 4.0 practices through PCA-Fuzzy AHP-K means

The Influence of Resources on Competitive Advantage through Clustering in Printing Companies in JABODETABEK

Optimization of Vehicle Transportation Route Based on IoT

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