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Simulation-based optimization is a decision-making tool for identifying an optimal design of a system. Here, optimal design means a smart system with sensing, computing and control capabilities with improved efficiency. As compared to testing the physical prototype, computer-based simulation provides much cheaper, faster and lesser time-and resource-consuming solutions. In this work, a comparative analysis of heuristic simulation optimization methods (genetic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed.

In this work, a comparative analysis of heuristic simulation optimization methods (genertic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed. Further, a novel simulation annealing-based heuristic approach is proposed for critical infrastructure.

A small scale network of 50–100 nodes shows that genetic simulation optimization with multi-criteria and multi-dimensional features performs better as compared to other simulation optimization approaches. Further, a minimum of 3.4 percent and maximum of 16.2 percent improvement is observed in faster route identification for small scale Internet-of-things (IoT) networks with simulation optimization constraints integrated model as compared to the traditional method.

In this work, simulation optimization techniques are applied for identifying optimized Quality of service (QoS) parameters for critical infrastructure which in turn helps in improving the network performance. In order to identify optimized parameters, Tabu search and ant-inspired heuristic optimization techniques are applied over QoS parameters. These optimized values are compared with every monitoring sensor point in the network. This comparative analysis helps in identifying underperforming and outperforming monitoring points. Further, QoS of these points can be improved by identifying their local optimum values which in turn increases the performance of overall network. In continuation, a simulation model of bus transport is taken for analysis. Bus transport system is a critical infrastructure for Dehradun. In this work, feasibility of electric recharging units alongside roads under different traffic conditions is checked using simulation. The simulation study is performed over five bus routes in a small scale IoT network.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.

There is a strong inducement to develop new inorganic materials to substitute the current industrial pigments, which are known for their poor ultraviolet absorbent and low photoluminescence (PL) properties. The purpose of this paper is to invent a better rare-earth-based pigment material as a spectral modifier with good luminescence properties to enhance the spectral response for photovoltaic panel application.

Different phosphor samples made of nano-calcium carbonate (CaCO₃) with varied wt.% of the dopant Dysprosium doped calcium borophosphate (CBP/Dy) as (W0 – 0%, W1 – 3,85%, W2 – 7.41%, W3 –10.71% and W4 –13.79%) were prepared via the solid-state diffusion method at 600 °C for 6 h using a muffle furnace. The structural, morphological and luminescence properties of the CaCO₃:CBP/Dy powder samples were examined using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and PL test.

The XRD, SEM and FTIR results verified the crystalline formation, morphological behaviour and vibration bonds of synthesized CBP/Dy-doped CaCO₃ powder samples. XRD pattern revealed that the synthesized powder samples exhibit crystalline structured materials, and SEM results showed irregular shape and porous-like structured morphologies. FTIR spectrum shows prominent bands at 712, 874 and 1,404 cm⁻¹, corresponding to asymmetric stretching vibrations of CO3²⁻ groups and out-of-plane bending. PL characterization of CBP/Dy-doped CaCO₃ (sample W) shows emission at 427 nm (λmax) under the excitation of 358 nm. The intensity of PL emission spectra drops due to the concentration quenching effect, while the maximum PL intensity is observed in the W3 phosphor powder system.

This phosphor powder is expected to find out the potential application such as a spectral modifier which is applied to match the energy of photons with solar cell bandgap to improve spectral absorption and lead to better efficiency.

The introduction of a nano-CaCO₃:CBP/Dy hybrid powder system with good luminescence properties to be used as spectral modifiers for solar cell application has been synthesized in the lab, which is a novel attempt.

Agility and sustainability are different manufacturing paradigms. Ideally, companies should merge the two concepts so as to enhance competitive advantage. Agility, which has evolved from lean manufacturing, is the ability of an enterprise to respond quickly to a wide range of customer demands. On the other hand sustainability is a condition in which a company optimizes economic, social and environmental factors by taking into account indirect and long-term consequences. Merging the two concepts could result in holistically improving the system, by fulfilling performance without depleting available resources. Thus, identifying and simultaneously improving two areas with common goals could lead to developing a successful and an emerging enterprise. The paper aims to discuss these issues.

The authors identify agility-sustainability criteria which complement each other from amongst a set of differentiating criteria. The conceptual model is built by integrating five enablers with 25 criteria and 75 attributes. The combined criteria are modeled using graph theory which considers interdependencies and contributing factors on the organization. Within each enabler, the authors investigate the interdependencies between criteria and focus further on those that have potential to improve overall score. The methodology was applied in a manufacturing organization that operates on ad hoc basis depending on projects’ availability.

The model determines a range of values for extreme scenarios under theoretical and practical situations, along with the current level of business. The scenarios are tested for assessing performance by identifying the gaps in the weaker areas.

Approach can serve as a managerial tool for monitoring performance of the organization along agility and sustainability dimensions. Further, government entities can use the approach in devising policy for improving economies by considering holistic approach rather than only environmental aspect. Biased and conflicting opinions of experts might deter chances for comprehensive and consistent decision.

The study integrates a framework for modeling and performance evaluation for a system that incorporates agility and sustainability characteristics. The study will enable practicing managers and decision makers to identify suitable characteristics that would simultaneously improve an organization’s agile performance by considering aspects of sustainability.

The current natural language processing algorithms are still lacking in judgment criteria, and these approaches often require deep knowledge of political or social contexts. Seeing the damage done by the spreading of fake news in various sectors have attracted the attention of several low-level regional communities. However, such methods are widely developed for English language and low-resource languages remain unfocused. This study aims to provide analysis of Hindi fake news and develop a referral system with advanced techniques to identify fake news in Hindi.

The technique deployed in this model uses bidirectional long short-term memory (B-LSTM) as compared with other models like naïve bayes, logistic regression, random forest, support vector machine, decision tree classifier, kth nearest neighbor, gated recurrent unit and long short-term models.

The deep learning model such as B-LSTM yields an accuracy of 95.01%.

This study anticipates that this model will be a beneficial resource for building technologies to prevent the spreading of fake news and contribute to research with low resource languages.

This paper aims to explore prisoner dental health in Haryana, India.

The authors assessed the prevalence of dental caries and the treatment needs of prisoners in all 19 prisons in Haryana. The results were compared with the prison populations of other countries and the general population of Haryana.

The mean age of 1,393 subjects examined was 35.26±12.29 years. A large number of the subjects reported to be in need of dental treatment. The number of decayed teeth was found to be similar to the general population of Haryana but the number of filled teeth was quite low. The number of teeth missing and the need for tooth extraction was high.

Long‐standing prisoner dental problems indicated a need for dental treatment in prisons.

This is the first study of its kind covering all 19 prisons in Haryana, India. The results indicate that the government needs to further consider and address the oral health needs of prisoners.

The learning outcomes of this paper are follows: students should be able to understand the complexity related to the provision of safe drinking water for disaster-hit areas and effective solutions to overcome this problem. Also, students should be able to evaluate the need for awareness about post traumas mental health especially in case of disasters and identify how technology can provide answers to such critical issues.

The case represents a unique scenario where the head of an organization has moved away from the financial prospect and invested time and efforts for the provision of safe drinking water to the inaccessible areas and devise strategies for the improvement of disaster relief operations.

Undergraduate and post graduate students.

Teaching notes are available for educators only.

CSS 4: Environmental Management.

The “quality” of any product or service defines the agility of the product and its life cycle in dynamic environment. The demand of high “quality” becomes an imperative concern, when “software” is acting as a product or a service. Since the nature of the software is intangible and more complex, therefore the assurance of providing accurate results is anxiety for companies. The overall quality of the software is based upon many individual factors (or attributes) that makes software reliable, inclined and a long-lasting product in the marketplace. But how these factors can influence each other is significant to identify. Therefore, the purpose of this paper is to study the quality aspect of the software and analyse the interrelationship of impactful attributes.

The analysis has been done through responses sought from software development teams/clients in India. The questionnaire related to the software quality was administered to the sample population. Interconnection among impactful characteristics has been analysed by using a qualitative technique called interpretive structural modelling (ISM). The driving and dependency of the attributes under consideration has been classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis. The procedure of applying ISM method has been automated and provided it as package “ISM” using R software.

In general, it is very complex job to determine the most impactful attribute of software quality. By applying ISM and MICMAC analysis on the set of attributes under consideration, it has been found that “reliability” along with “usability” and “performance” is the most influential attribute of software quality and preferred most.

Though ISM provides an organized modelling framework yet its results are considered less statistically significant. Therefore, it would be interesting to concatenate the present findings with the findings of any analytical methodology; which gives statistically significant results.

The present proposal deals with the interpretation of the software quality attributes and their contextual relationship but with more effective and efficient manner. It can help management to understand the complexity of relationship amongst attributes (which are quality attributes here) more accurately and precisely. Since today is an era of automation, the manual part is being substituted so as to reduce the labour cost, improve safety, security and product quality to increase production. This study is, therefore, an effort and a helping hand in making the hassle free calculations for obtaining intermediate matrices and doing eventual calculations.

n numbers of parameters can be selected to analyse the interrelationship of any project/study. Eradication human errors in applying transitivity law or applying any other operation in solving problem. The package created here can save precious time of users. Provides well-formatted and readable excel output files that make interpretation easier.

Software is one such product/service which plays a significant role in this high-technological world, where each and every firm try their best to be on the top of the list of consumers’ preference. For this purpose, companies reduce manual efforts by converting it into qualitative software that provides deliverables in a systematic manner. Therefore, it becomes imperative to study various interrelated quality attributes of the software. On the similar platform, ISM is a widely used technique and just to provide a helping hand in quantification of the qualitative attributes this paper facilitates the readers with algorithm developed using R software.

In early 2017, after launching its successful “Greenhouse-in-a-Box” pilot project in India with fifteen smallholder farmers, Kheyti, a non-profit agricultural technology (AgTech) social enterprise, was struggling with several decisions in developing and growing its business. Kheyti was launched in 2015 to help smallholder farmers battle poverty and income variability by providing affordable technologies bundled with services. Over eighteen months, the team had developed a low-cost and modular greenhouse product to which it added financing, inputs, training, and market linkages to create a comprehensive “full-stack” solution for small farmers. The pilot project was a success in many ways, but Saumya, Kheyti's co-founder and head of product, was concerned that it revealed shortcomings that could severely affect the viability and scalability of Kheyti's solution.

Saumya had some important decisions to make. Should Kheyti redesign the product from scratch, or find other ways to reduce the cost for early adopters? Should it rely on upfront revenues from sales of the greenhouse, or consider developing an innovative financing or contract farming model? Kheyti's dwindling cash reserves meant that these decisions were urgent and critical. The path chosen now would determine whether the startup would move beyond the pilot stage and achieve its vision of serving 1 million farmers by 2025.