Automatic guided vehicle system (AGVs) plays a vital role in material handling operations for a flexible manufacturing system (FMS).Optimum AGVs fleet size selection is one of the most sig-nificant decisions in effective design and control of automated material handling system. The fleet size estimation and optimization of AGVs requires an in-depth understanding of the various factors that AGVs in the FMS relies on. In this paper, an investigation for fleet size optimization of AGVs in different layouts of FMS by application of the analytical method and grey wolf optimization al-gorithm (GWO) is carried out. Layout design is one of the significant factors for optimization of AGV’s fleet size in any FMS. Results yield from analytical and grey wolf optimization algorithm are compared and validated for the different sizes of FMS layouts by computational experiments.

Lamotrigine (LMT), chemically known as [6-(2,3-dichlorophenyl)-1,2,4-triazine-3,5-diamine], is a broad spectrum antiepileptic drug, used as monotherapy and as an adjunct with other antiepileptic drugs for treatment of partial and generalized toxic-clonic seizures. It is used to treat neurological lesions and as a tranquilizer. A selective electrochemical membrane sensor has been developed and validated for determination of LMT. The membrane constructed using LMT and molybdophosphoric acid in THF and PVC is applicable for the detection of 5 × 10^-4 to 9 × 10^-3 M LMT in the pH range between 4.6 and 5.8 with the Nernstian slope of 57.14±1 mV/decade. The regression coefficient value of 0.9932 showed a good linear correlation between the concentrations of LMT and measured cell potentials. The limits of detection (LOD) and quantification (LOQ) values for the fabricated sensor were 1.3 × 10^-5 and 4 × 10^-5 M LMT, respectively. Various experimental conditions were optimized to reach the effective performance characteristics of the sensor. The effect of various cations, anions and organic species on the performance of sensor was studied by following standard-addition procedure. The results revealed no such variations due to presence of foreign ions or species. The fabricated sensor was subjected to validation to check accuracy, precision, robustness and ruggedness. The mean accuracy for determination of LMT was found to be 99.16%. The developed sensor was successfully used to determine LMT in tablets and in spiked human urine.

This paper introduces a novel practical variant, namely an open close multiple travelling salesmen problem with single depot (OCMTSP) that concerns the generalization of classical travelling salesman problem (TSP). In OCMTSP, the overall salesmen can be categorized into internal/permanent and external/outsourcing ones, where all the salesmen are positioned at the depot city. The primary objective of this problem is to design the optimal route such that all salesmen start from the depot/base city, and then visit a given set of cities. Each city is to be visited precisely once by exactly one salesman, and only the internal salesmen have to return to the depot city whereas the external ones need not return. To find optimal solutions, an exact pattern recognition technique based Lexi-search algorithm (LSA) is developed which has been subjected in Matlab. Comparative computational results of the LSA have been made with the existing methods for general multiple travelling salesman problem (MTSP). Further, to test the performance of LSA, computational experiments have been carried out on some benchmark as well as randomly generated test instances for OCMTSP, and results are reported. The overall computational results demonstrate that the proposed LSA is efficient in providing optimal and sub-optimal solutions within the considerable CPU times.

The mobility sector including all kinds of transportation systems are facing global challenges in re-spect of green environmental issues. There has been a paradigm shift in the concept of design and manufacturing of automotive vehicles keeping in mind the scarcity of fossil fuel and the impact of emission on environment due to burning of it. The addition of hybrid and electric vehicles in pas-senger car segment has got significant momentum to address the global challenges. This research investigates the performance of a group of hybrid vehicles from customers’ perspective. Among the different brands that are available in the hybrid vehicle market, smart customers have given pri-ority to vehicle cost, mileage, tail pipe emission, comfortness and high tank size volume for long drive. Considering these attributes, selection strategy for hybrid vehicles has been developed using entropy based multi-attributive border approximation area comparison (MABAC) method. This research highlights the best hybrid vehicle which reduces air pollution in cities with other significant environmental benefits, reduces dependence on foreign energy imports and minimizes the annual fuel cost.

Stochastic optimization algorithm provides a robust and efficient approach for solving complex real world problems. Backtracking Search Optimization Algorithm (BSA) is a new stochastic evolutionary algorithm and the aim of this paper is to introduce a hybrid approach combining the BSA and Quadratic approximation (QA), called HBSAfor solving unconstrained non-linear, non-differentiable optimization problems. For the validity of the proposed method the results are compared with five state-of-the-art particle swarm optimization (PSO) variant approaches in terms of the numerical result of the solutions. The sensitivity analysis of the BSA control parameter (F) is also performed.

A note published by Chinta et al. (2016) [Chinta, S., Kommadath, R. & Kotecha, P. (2016) A note on multi-objective improved teaching–learning based optimization algorithm (MO-ITLBO). Information Science, 373, 337-350.] reported some impediments in implementation of MO-ITLBO algorithm. However, it is observed that their comments are based on incorrect understanding of TLBO, ITLBO and MO-ITLBO algorithms. Their raised issues are thoroughly addressed in this paper and it is proved that MO-ITLBO algorithm has no lacunae.

The objective of the present work is to use a suitable method that can optimize the process parameters like pulse on time (TON), pulse off time (TOFF), wire feed rate (WF), wire tension (WT) and servo voltage (SV) to attain the maximum value of MRR and minimum value of surface roughness during the production of a fine pitch spur gear made of copper. The spur gear has a pressure angle of 20⁰ and pitch circle diameter of 70 mm. The wire has a diameter of 0.25 mm and is made of brass. Experiments were conducted according to Taguchi’s orthogonal array concept with five factors and two levels. Thus, Taguchi quality loss design technique is used to optimize the output responses carried out from the experiments. Another optimization technique i.e. desirability with grey Taguchi technique has been used to optimize the process parameters. Both the optimized results are compared to find out the best combination of MRR and surface roughness. A confirmation test was carried out to identify the significant improvement in the machining performance in case of Taguchi quality loss. Finally, it was concluded that desirability with grey Taguchi technique produced a better result than the Taguchi quality loss technique in case of MRR and Taguchi quality loss gives a better result in case of surface roughness. The quality of the wire after the cutting operation has been presented in the scanning electron microscopy (SEM) figure.

The objective of this research is to comprehend how these elements interact to influence young people's subjective happiness and to provide insightful information about their perspectives. Significant discoveries are shown by the study's findings. This research paper conducts a thorough analysis of the many factors that affect youth happiness, including GDP, loneliness, longevity, autonomy, generosity, and corruption. First off, GDP shows up as a significant and noticeably positive factor to young happiness. This emphasizes how crucial economic success is in raising young people's life happiness. Second, autonomy is recognized as another important factor, showing a significant and favorable influence on happiness. It emphasizes how important one's own independence and life control are for young wellbeing. Additionally, the study uncovers a diverse range of impacts among these indicators. Longevity and Generosity are found to positively influence happiness, emphasizing the role of health and social support in young people's contentment. Conversely, Loneliness and Corruption exhibit significant negative effects on happiness, underscoring the detrimental consequences of social isolation and institutional corruption on youth well-being. In conclusion, this research paper offers a holistic view of youth happiness, recognizing the multifaceted nature of its determinants. These findings have important implications for policymakers, highlighting the need to address not only economic aspects but also personal autonomy, social connectedness, and integrity in efforts to promote youth happiness and well-being in society.

Two heterocyclic oximes (E)-N-hydroxy-1-(pyridin-2-yl)methanimine (Hp2ylm) and (E)-N-hydroxy-1-(pyridin-3-yl)methanimine (Hp3ylm) were synthesized from pyridine-2-carbaldehyde and pyridine-3-carbaldehyde, respectively. These oximes were characterized by various spectroscopic tools like UV, IR, MASS and NMR. The inhibition capacity of these oximes against copper corrosion in 0.1 M HNO3 was determined by polarization and impedance spectroscopic studies (EIS). At all concentrations, Hp3ylm exhibited higher inhibition efficiency than Hp2ylm. Attempt was made to illustrate the mechanism of corrosion inhibition by these oximes with the help of adsorption isotherm, scanning electron microscopic (SEM) and quantum chemical studies.

Turning experiments were conducted on a novel aluminum alloy (LM6)/fly ash composite based on the response surface and face centered central composite design methodology. The effects of cutting parameters on surface roughness and tool wear were investigated. Multiple regression models were developed for the responses and the adequacies of the developed models were tested at 95% confidence interval using the analysis of variance (ANOVA) technique. Carbide inserts (Model: CNMG 120408-M5) were used for turning the specimens in a CNC turning machine (model: LT-16). The test for significance of the regression models, the test for significance on individual model coefficients and the lack-of-fit tests were performed using the statistical Design-Expert7.0v software environments. R2 indicated the model significance and the value was more than 97%, revealed that the relation between cutting responses and input parameters held good for more than 97% and the model was adequate.