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Prabhat Kumar College

About: Prabhat Kumar College is a based out in . It is known for research contribution in the topics: Schiff base & Scalar field. The organization has 39 authors who have published 109 publications receiving 574 citations.


Papers
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Journal ArticleDOI
TL;DR: In this paper, two dyes, namely rhodamine and azobenzene, have been conjugated for the detection of Al3+ in aqueous ethanol.
Abstract: The high absorption coefficient, fluorescence quantum yield, photo stability and relatively long wavelengths of rhodamine dye have expanded its applicability as a promising fluorescent probe. In the present investigation, two dyes, namely rhodamine and azobenzene, have been conjugated for the detection of Al3+ in aqueous ethanol. The turn on fluorescence response of chemosensor L towards Al3+ is attributed to the inhibited PET (photo-induced electron transfer) and CHEF (chelation enhanced fluorescence) process along with the spirolactam (non-fluorescent) to ring-opened amide (fluorescent) process. The presence of the PET and CHEF process was corroborated by time-resolved photoluminescence study and the spirolactam ring opening was confirmed by 13C NMR and infrared spectroscopy. In the presence of Al3+, the opened spirolactam ring forms a 1 : 1 binding complex with the metal, which is supported by its high binding constant (Ka = 7.033 × 103 M−1). The limit of detection (LOD) and limit of quantification (LOQ) values are found to be 1.1 × 10−7 M and 3.6 × 10−7 M, respectively. The reversible recognition of Al3+ was also proved in the presence of Na2EDTA by both UV-Vis and fluorometric titration. The sensing behaviour of the chemosensor towards Al3+ was supported by DFT/TDDFT calculations.

36 citations

Journal ArticleDOI
TL;DR: An ''economic production lot size'' (EPLS) model for an item with imperfect quality is developed by considering random machine failure and sensitivity of the nearer optimal solution due to changes of some key parameters are analysed.
Abstract: An ''economic production lot size'' (EPLS) model for an item with imperfect quality is developed by considering random machine failure. Breakdown of the manufacturing machines is taken into account by considering its failure rate to be random (continuous). The production rate is treated as a decision variable. It is assumed that some defective units are produced during the production process. Machine breakdown resulting in idle time of the respective machine which leads to additional cost for loss of manpower is taken into account. It is assumed that the production of the imperfect quality units is a random variable and all these units are treated as scrap items that are completely wasted. The models have been formulated as profit maximization problems in stochastic and fuzzy-stochastic environments by considering some inventory parameters as imprecise in nature. In a fuzzy-stochastic environment, using interval arithmetic technique, the interval objective function has been transformed into an equivalent deterministic multi-objective problem. Finally, multi-objective problem is solved by Global Criteria Method (GCM). Stochastic and fuzzy-stochastic problems and their significant features are illustrated by numerical examples. Using the result of the stochastic model, sensitivity of the nearer optimal solution due to changes of some key parameters are analysed.

36 citations

Journal ArticleDOI
TL;DR: This paper presents a production lot size inventory model in which the production rate constitutes of productions during both regular time and overtime, and the demand rate is assumed as stock-dependent and the stock itself is depleted due to demand and deterioration.
Abstract: This paper presents a production lot size inventory model in which the production rate constitutes of productions during both regular time and overtime. The demand rate is assumed as stock-dependent and the stock itself is depleted due to demand and deterioration. Supplier's incentives include price discounts and granting of credit periods for account settlement within time M"1, or the supplier allows interest-free credit upto an extended period M"2. This formulation leads to a single objective optimization problem for maximum average profit evaluation through a real-coded genetic algorithm (GA) with rank-based selection and arithmetic crossover. The model is illustrated through a numerical example, and sensitivity analyses have been done with the variation of demand and deterioration parameters on optimal profit.

33 citations

Journal ArticleDOI
TL;DR: This paper develops a production-inventory model for a deteriorating item with stock-dependent demand under two storage facilities over a random planning horizon, which is assumed to follow exponential distribution with known parameter.
Abstract: This paper develops a production-inventory model for a deteriorating item with stock-dependent demand under two storage facilities over a random planning horizon, which is assumed to follow exponential distribution with known parameter. The effects of learning in set-up, production, selling and reduced selling is incorporated. Different inflation rates for various inventory costs and time value of money are also considered. A hybrid genetic algorithm is designed to solve the optimization problem which is hard to solve with existing algorithms due to the complexity of the decision variable. To illustrate the model and to show the effectiveness of the proposed approach a numerical example is provided. A sensitivity analysis of the optimal solution with respect to the parameters of the system is carried out.

28 citations

Journal ArticleDOI
05 May 2019
TL;DR: The proposed NMGA is the combination of Boltzmann probability selection and a multi-parent crossover technique with known random mutation to solve the Traveling Salesman Problem.
Abstract: In the present study, a Novel Memetic Genetic Algorithm (NMGA) is developed to solve the Traveling Salesman Problem (TSP). The proposed NMGA is the combination of Boltzmann probability selection and a multi-parent crossover technique with known random mutation. In the proposed multi-parent crossover parents and common crossing point are selected randomly. After comparing the cost/distance with the adjacent nodes (genes) of participated parents, two offspring’s are produced. To establish the efficiency of the developed algorithm standard benchmarks are solved from TSPLIB against classical genetic algorithm (GA) and the fruitfulness of the proposed algorithm is recognized. Some statistical test has been done and the parameters are studied.

28 citations


Authors
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20221
202128
202024
201918
20189
20174