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Optimal procurement and pricing policy for deteriorating items with price and time dependent seasonal demand and permissible delay in payment
In practice, items like food, nursery plants, medicines, etc. are seasonal and deteriorating in nature. For this type of products, permissible delay in payment is a common business policy, which is used to increase in the sell volume and to develop trust in buyer-seller relationship. In this paper, we developed an inventory model for time dependent deteriorating seasonal items with the permission of delay in payment. Shortages are permitted and partially back ordered. Our aim is to find optimal selling price and ordering quantity simultaneously. Concavity of profit function with respect to decision variables has been discussed analytically. A solution procedure followed by a numerical example and sensitivity analysis along with managerial insights are provided. Numerical analysis predicts that delay in payment profit policy is a better decision in order to maximise the profit or in order to get more profit. 2022 Inderscience Enterprises Ltd. -
Optimal portfolio construction with nifty stocks /
International Journal of Interdisciplinary and Multidisciplinary Studies, Vol.1, Issue 4, pp.474-480, ISSN No: 2348-0343. -
Optimal ordering and discounting policy for a segmented market with price and freshness dependent demand for mixed quality product
Owing to various factors, fresh produce purchased by the retailer is initially of mixed quality. A random proportion of the lot would generally have lost some freshness before being received in stock, while the remaining items would still be fresh. This calls for some discount initially for the former, and later, when the latter product is not so fresh. For demand declining with increase in selling price and decrease in freshness, this paper deals with optimal ordering and discounting policy when the lot received is of mixed quality and the market has two segments differentiated by the initial product quality sold simultaneously at widely different prices. Sufficient conditions for existence and uniqueness of optimal cycle length and the optimal discount are obtained. Sensitivity analysis reveals that increase in freshness time and proportion of initially fresh items in the lot result in increased profit rate. Copyright 2024 Inderscience Enterprises Ltd. -
Optimal order quantity with endogenous discounted partial advance payment and trade-credit for inventory model with linear time varying demand
When buyers seek extended credit periods from relatively less secure suppliers, the supplier requires co-operation from the buyer for purchase of raw materials, etc., in terms of partial advance payment. For a single buyer single supplier supply chain, we develop an inventory model with a hybrid payment policy combining discounted advance payment to supplier with the supplier permitting interest free delay period to the buyer when buyer has the option to make advance payment. For the advance, supplier offers discount and may allow the buyer to set the discount rate and the advance proportion. For a linear demand function in such a scenario, we maximise buyer's net profit rate through optimal choice of payment policy and the buyer's replenishment. We consider two situations with discount: 1) exogenous; 2) endogenous for the buyer. Optimal solution is characterised theoretically. Numerical example reveals that by choosing advance proportion appropriately, the profit rate in the endogenous case can be higher than that in the exogenous case even with lower discount. 2021 Inderscience Enterprises Ltd.. All rights reserved. -
Optimal Management of Resources in Cloud Infrastructure through Energy Aware Collaborative Model
As the infrastructures of cloud computing provides paramount services to worldwide users, persistent applications are congregated using large scale data centres at the customer sides. For such wide platforms, virtualization technique has been incorporated for multiplexing the essential sources available. Due to the extensive application variations in the workloads, it is significant to handle the resource allocation methodologies of the virtual machines (VM) for assuring the Quality of Service (QoS) of cloud. On concentrating this, the paper proposed a Decentralized Energy-Aware Collaborative Model (DEACM) for effectively managing the data centres in cloud infrastructures. Initially, the optimal model for system management and power management are declared. Then, functions of workload vectors and data collection about workloads has been carried out for optimal selection of virtual machines to migrate for balancing loads efficiently. This can be further applied for Target-based VM Migration Algorithm for determining the migrating target for VM. Moreover, the algorithm involved in energy utilization with managed QoS. The developed DEACM is evaluated using CloudSim platform and the results are discussed. The results exemplify that the DEACM can balance the workload across variety of machines optimally and provide reduced energy consumption to the complete system efficiently. 2024 IEEE. -
Optimal locations for PMUs maintaining observability in power systems
Population of Phasor Measurement Units (PMUs) in power systems are increasing day by day as PMUs measure the electrical quantities more accurately with time-stamping. The measurements done by PMU can be used for monitoring, controlling and for state estimation of the power system. Since the installation of PMUs demand high capital cost, their number and location to be chosen optimally is by minimizing investment without losing observability of the system. In this paper Integer Programming techniques used to solve Optimal Placement of PMU (OPP) problem. The OPP problem is solved for normal power system as well as for a few contingency conditions like one PMU outage, considering zero injection bus, outage of single line on various standard IEEE Bus Systems. The work is also trying to place PMUs under planned islanding in certain standard networks. 2016 IEEE. -
Optimal location and parameters of GUPFC for transmission loss minimization using PSO algorithm
Transmission losses are one of the major losses faced by our power system. Reduction of transmission losses will benefit us by saving a large amount of power. The transmission losses can be reduced by placing FACTS devices in the power system. Among all the FACTS devices Unified Power Flow Controller (UPFC) and Generalized Unified Power Flow Controller (GUPFC) are the best. Incorporating the GUPFC in to the power system and placing it to the optimal location and setting its output to optimal values can reduce the transmission losses. This paper explains the way to locate the optimal location of GUPFC and finding the optimal setting using PSO algorithm to reduce the total transmission losses. Voltage variation is taken as the criteria for finding the location and PSO is used for finding the settings of GUPFC. This study is conducted on an IEEE 14-bus system using MATLAB software. 2017 IEEE. -
Optimal Load Control for Economic Energy Equilibrium in Smart Grid Using Adaptive Inertia Weight Teaching-Learning-Based Optimization
Due to numerous operational restrictions and economic purposes, optimal load management for energy balance in the smart grid (SG) is one of the compensating responsibilities. This research provides a novel multiobjective optimization technique for attaining energy balance in SG, with the goal of avoiding fines due to excessive upstream network power extraction beyond contractual demand. Due to a lack of capacity to create the whole optimization towards the global optimum after each run, optimal load control (OLC) is a prevalent challenge. Adaptive-TLBO, the most recent variation of Teaching Learning Based Optimization (TLBO), comprises both alterations during the exploitation and exploration phases (ATLBO). Because the ATLBO is used on a modified IEEE 33-bus system, the results obtained in this mode are extraordinary. The energy balance has improved in addition to the enhancement of the voltage profile and the reduction of distribution losses. As evidenced by comparisons with PSO, basic TLBO, backtracking search algorithm (BSA), and cuckoo search algorithms, the suggested ATLBO algorithm has precedence over any other proposed algorithm (CSA) 2022, International Journal of Intelligent Engineering and Systems.All Rights Reserved. -
Optimal Feature Selection for the Classification of Hyperspectral Imagery Using Adaptive SpectralSpatial Clustering
Hyperspectral images captured through the hyperspectral sensors play an imperative part in remote sensing applications in the present context. Unlike traditional images sensed with few bands in the visible spectrum, the hyperspectral (HS) images are obtained with hundreds of spectral band ranges from infrared to ultraviolet regions. Because of its vast spatial and spectral data, it requires an extensive computational system for processing and its hidden features are needed to be unveiled in an effective manner specifically for the classification of HS imagery. This approach exploits the high spectral band correlation and rich spatial information of the HS images for the generation of feature vectors. To attain optimal feature space for the best probable classification, an adaptive approach is incorporated to adaptively choose spectralspatial features for feature selection to classify the pixels effectively. Furthermore, the HS image encompasses several bands including noisy bands. To categorize the images with great accuracy, it is suggested to eradicate the noisy bands whilst retaining the informative bands. In this research, an adaptive spectralspatial feature selection scheme is proposed for HS images where the extremely correlated representative bands are considered for analysis with uncorrelated and noisy spectral bands are judiciously discarded during its classification process. This hybrid approach not merely diminishes the computational time and also improves the general classification accuracy significantly. The empirical result displays that the proposed work surpasses the conventional approach of HS image classification systems. 2018, Springer Science+Business Media, LLC, part of Springer Nature. -
Optimal Disassembly Sequence Generation Using Tool Information Matrix
Just as the assembly sequence plays an important role in the early part of the product, the disassembly sequence plays an important part in the final stage of the product. The disassembly sequence determines how efficiently the product can be recycled or it can be disassembled for maintenance purposes. In this study, the disassembly sequence is generated using the Tool Information Matrix (TIM) and the contact relations. In this study the feasible sequences are generated using the TIM and contact relations, afterward, the time required is considered as a fitness equation for generating the optimal disassembly sequence. The proposed methodology is applied to 10-part crankshaft assembly to test the performance in generating the optimal disassembly sequences. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Optimal DG Planning and Operation for Enhancing Cost Effectiveness of Reactive Power Purchase
The demand for reactive power support from distributed generation (DG) sources has become increasingly necessary due to the growing penetration of DG in the distribution network. Photovoltaic (PV) systems, fuel cells, micro-turbines, and other inverter-based devices can generate reactive power. While maximizing profits by selling as much electricity as possible to the distribution companies (DisCos) is the main motive for the DG owners, technical parameters like voltage stability, voltage profile and distribution losses are of primary concern to the (DisCos). Local voltage regulation can reduce system losses, improve voltage stability and thereby improve efficiency and reliability of the system. Participating in reactive power compensation reduces the revenue generating active power from DG, thereby reducing DG owners profits. Payment for reactive power is therefore being looked at as a possibility in recent times. Optimal power factor (pf) of operation of DG becomes significant in this scenario. The study in this paper is presented in two parts. The first part proposes a novel method for determining optimal sizes and locations of distributed generation in a radial distribution network. The method proposed is based on the recent optimization algorithm, TeachingLearning-Based Optimization with Learning Enthusiasm Mechanism (LebTLBO). The effectiveness of the method has been compared with existing methods in the literature. The second part deals with the determination of optimal pf of operation of DG sources to minimize reactive power cost, reduce distribution losses and improve voltage stability. The approachs effectiveness has been tested with IEEE 33 and 69 bus radial distribution systems. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Optimal design of controller for automatic voltage regulator performance enhancement: a survey
For regulating the Synchronous Generator (SG) output voltage, the Automatic Voltage Regulator (AVR) system is a significant device. This work propounds a survey on Optimization Algorithms (OAs) utilized for tuning the controller parameters on the AVR system. A device wielded for adjusting the SGs Terminal Voltage (TV) is named AVR. A Controller is utilized for improving stability and getting a superior response by mitigating maximum Over Shoot (OS), reducing Rise Time (RT), reducing Settling Time (ST), and enhancing Steady State Error (SSE) since output voltage has a slower response and instability. The controllers utilized here are Proportional-Integral-Derivative (PID), Intelligent Controller (IC), along with Fraction Order PID (FOPID). Owing to the occurrence of time delays, nonlinear loads, variable operating points, and others, OAs are wielded for tuning the controller. (a) Particle Swarm Optimization (PSO), (b) Genetic Algorithm (GA), (c) Gray Wolf Optimizer (GWO), (d) Harmony Search Algorithm (HSA), (e) Artificial Bee Colony (ABC), (f) Teaching Learned Based Optimization (TLBO), et cetera are the various sorts of OA. For enhancing the TV response along with stability, various OAs were tried by researchers. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser
The burden on the consumer for the price of fuel for classic vehicles is the root cause for the emergence of the fast growing trend in the power driven vehicles or electric vehicles. Less acceptance of electric vehicles by the customers and the hesitancy to replace traditional fuel powered vehicles by considering the economic factor is a major concern that existing in the current scenario. Therefore, for the proper balancing of the load with respect to the power available among different neighbouring charging stations in a given area, a load scheduling algorithm is used. The optimal route planner for the electric vehicles reaching the charging station is identified and then the power carried by each feeder is calculated by cumulative power of all the charging stations. The identification of the possible route is performed by the spatial network analysis which will be executing at remote analyzer. The location, state of charge, and other details of the electric vehicle through telemetry is used to find the best charging station for the particular vehicle in view of the cost, distance and the time. The performance of the technique is evaluated with and without optimization by considering the logical constraints; and the results are presented. Springer Nature Switzerland AG 2020. -
Optimal Benchmarking of Quality of Service and Quality of Experience Metrics for Telecom Service Providers Using A Slack Based, Measure in Data Envelopment Analysis
With new devices and new network technologies coming up, it has become an inevitable task to provide services of a minimum quality. Setting feasible Service Level Agreements (SLAs) is the need of the hour. This, being a part of network provisioning and providing the best possible Quality of Service (QoS) is very vital and helps improve user perceived quality or the Quality of Experience (QoE). QoE evaluation helps Internet Service Providers (ISPs) understand their user satisfaction better and this goes hand in hand with providing adequate network QoS. Moreover, in this era of competition, the ISPs themselves will have to be evaluated based on their QoE and QoS metrics to know their true position in the market in terms of performance against their peers/competitors. This evaluation is usually done on a per-metric basis. However, we see from current performance data that all the ISPs fare well on some metrics and need improvement in the others. It is a fact that no ISP fares bad on all given metrics and leads to an understanding that per-metric based evaluation may be a biased form of newlineevaluating performance. Hence, this research has attempted to use an intelligent, robust newlinemathematical technique called the Data Envelopment Analysis (DEA) with its Slack newlineBased Measure (SBM) approach. DEA is a proven, tested and tried technique that is in newlineuse in major industries even today. Being a multiple criterion evaluation methodology newlinebased on linear programming, it works well on multiple outputs and multiple inputs. DEA gives the overall, relative efficiency of the ISPs which gives us the true position of the provider against its peers. The Slack Based Measure provides the Output Slacks that show the potential improvement that the lagging ISPs can make to be in par with their peers/competitors. The Output targets that are provided by the technique can be used as benchmarks for SLAs. -
Optimal benchmarking of quality of service and quality of experience metrics for telecom service providers using a slack based measure in data envelopment analysis
With new devices and new network technologies coming up, it has become an inevitable task to provide services of a minimum quality. Setting feasible Service Level Agreements (SLAs) is the need of the hour. This, being a part of network provisioning and providing the best possible Quality of Service (QoS) is very vital and helps improve user perceived quality or the Quality of Experience (QoE). QoE evaluation helps Internet Service Providers (ISPs) understand their user satisfaction better and this goes hand in hand with providing adequate network QoS. Moreover, in this era of competition, the ISPs themselves will have to be evaluated based on their QoE and QoS metrics to know their true position in the market in terms of performance against their peers/competitors. This evaluation is usually done on a per-metric basis. However, we see from current performance data that all the ISPs fare well on some metrics and need improvement in the others. It is a fact that no ISP fares bad on all given metrics and leads to an understanding that per-metric based evaluation may be a biased form of newlineevaluating performance. Hence, this research has attempted to use an intelligent, robust newlinemathematical technique called the Data Envelopment Analysis (DEA) with its Slack newlineBased Measure (SBM) approach. DEA is a proven, tested and tried technique that is in newlineuse in major industries even today. Being a multiple criterion evaluation methodology newlinebased on linear programming, it works well on multiple outputs and multiple inputs. DEA gives the overall, relative efficiency of the ISPs which gives us the true position of the provider against its peers. The Slack Based Measure provides the Output Slacks that show the potential improvement that the lagging ISPs can make to be in par with their peers/competitors. The Output targets that are provided by the technique can be used as benchmarks for SLAs.
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Optimal arrangement of ration items into container using modified forest optimization algorithm
Planning a shrewd framework for loading the ration goods into the container is one of the significant objectives in the mission of smart city advancement in India. This optimal container loading system is designed for the arrangement of ration goods into the container using Modified Forest Optimization algorithm for safe and secure delivery. The effectiveness of the proposed approach has been demonstrated using BR datasets and compared with different optimization algorithms. From the experiment, it is observed that the proposed Modified Forest Optimization algorithm is implemented in java meets the objective of loading the ration items into the container in an optimal fashion. Further, it is observed that the order of arrangement predicted by the proposed algorithm is found to be optimal than other competitive optimization algorithms. 2020, Engg Journals Publications. All rights reserved. -
Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm
This paper proposes to resolve optimal solar photovoltaic (SPV) system locations and sizes in electrical distribution networks using a novel Archimedes optimization algorithm (AOA) inspired by physical principles in order to minimize network dependence and greenhouse gas (GHG) emissions to the greatest extent possible. Loss sensitivity factors are used to predefine the search space for sites, and AOA is used to identify the optimal locations and sizes of SPV systems for reducing grid dependence and GHG emissions from conventional power plants. Experiments with composite agriculture loads on a practical Indian 22-bus agricultural feeder, a 28-bus rural feeder and an IEEE 85-bus feeder demonstrated the critical nature of optimally distributed SPV systems for minimizing grid reliance and reducing GHG emissions from conventional energy sources. Additionally, the voltage profile of the network has been enhanced, resulting in significant reductions in distribution losses. The results of AOA were compared to those of several other nature-inspired heuristic algorithms previously published in the literature, and it was observed that AOA outperformed them in terms of convergence and redundancy when solving complex, non-linear and multivariable optimization problems. The Author(s) 2022. -
Optimal Allocation of Renewable Sources with Battery and Capacitors in Radial Feeders for Reliable Power Supply Using Pathfinder Algorithm
Allocating renewable energy systems (RESs) in an electrical distribution system (EDS) is crucial to achieving various objectives. However, their intermittency presents several challenges. In this connection, an efficient meta-heuristic pathfinder algorithm (PFA) is employed to determine the optimal location and size of photovoltaic (PV) and wind turbine (WT) systems, along with energy storage systems (ESS) and capacitor banks (CB) for both grid and islanding modes of operations. An objective function was formulated for loss reduction, greenhouse gas (GHG) emissions, and voltage profile improvement. The simulation results for the IEEE 33-bus EDS system are shown for two cases: grid-connected and islanding. The computational effectiveness of the PFA was compared with that reported in the literature. The PFA results showed an outstanding ability to resolve difficult optimisation problems. In addition, the optimal size of the RES when the network operates in the grid-connected mode can significantly improve the performance. The real power losses and GHG emissions were reduced by 48.49 % and 67.75% with PV systems and the other, respectively, whereas WT systems they are reduced to 69.68 % and 67.85 %, respectively. However, a combination of ESS, CB, and PV/WT can render the EDN sustainable for the islanding mode of operations. The Author(s). -
Optimal allocation algorithm of marketing resources based on improved random forest
Random Forest algorithm is an ensemble learning algorithm that classifies data by combining multiple decision trees. It has a wide range of applications and is not easy to overfit. It has a wide range of applications in medicine, bioinformatics, management and other fields. By studying the Cobb-Douglas sales function, it is found that it can only analyze the static allocation of marketing resources, but cannot describe the dynamic changes. Enterprise marketing resource management runs through the enterprise management from beginning to end. The research on marketing resource management is helpful for enterprises to grasp and control the whole process of marketing resource management from the overall and overall level, and has important theoretical value and reality for enterprise marketing management activities. significance. In the vast majority of enterprises in our country, the size of advertising promotion expenses and the number of salesmen is often determined based on the experience and subjective assumptions of decision makers, so it is difficult to say that they are optimized. This paper starts with determining the optimal advertising budget and the number of salespeople, and conducts applied research on the optimal allocation of marketing resources. 2023 IEEE. -
Optical spectroscopy of Galactic field classical Be stars
In this study, we analyse the emission lines of different species present in 118 Galactic field classical Be stars in the wavelength range of 3800-9000 We re-estimated the extinction parameter (AV) for our sample stars using the newly available data from Gaia DR2 and suggest that it is important to consider AV while measuring the Balmer decrement (i.e. D34 and D54) values in classical Be stars. Subsequently, we estimated the Balmer decrement values for 105 program stars and found that ?20 per cent of them show D34 ? 2.7, implying that their circumstellar disc are generally optically thick in nature. One program star, HD 60855 shows H? in absorption - indicative of disc-less phase. From our analysis, we found that in classical Be stars, H? emission equivalent width values are mostly lower than 40 which agrees with that present in literature. Moreover, we noticed that a threshold value of ?10of H? emission equivalent width is necessary for FeII emission to become visible. We also observed that emission line equivalent widths of H?, P14, FeII 5169, and OI 8446for our program stars tend to be more intense in earlier spectral types, peaking mostly near B1-B2. Furthermore, we explored various formation regions of Ca II emission lines around the circumstellar disc of classical Be stars. We suggest the possibility that Ca II triplet emission can originate either in the circumbinary disc or from the cooler outer regions of the disc, which might not be isothermal in nature. 2021 Oxford University Press. All rights reserved.