A TSSA algorithm based approach to enhance the performance of warehouse system

In this plethora of increased competitiveness and globalization the effective management of the warehouse system is a challenging task. Realizing that proper scheduling of the warehouses is necessary to outperform the competitors on cost, lead time, and customer service basis (Koster, 1998); the proposed research focuses on optimization of warehouse scheduling problems. This research aims to minimize the total tardiness so that the overall time involved in managing the inventory inside the warehouse could be effectively reduced. This research also deals with the vehicle routing issues in the warehousing scenario and considers various constraints, and decision variables, directly influencing the undertaken objective so as to make the model more realistic to the real world environment. The authors have also proposed a hybrid tabu sample-sort simulated annealing (TSSA) algorithm to reduce the tardiness as well as to enhance the performance of the warehousing system. The proposed TSSA algorithm inherits the merits of the tabu search and sample-sort annealing algorithm. The comparative analysis of the results of the TSSA algorithm with other algorithms such as simulated annealing (SA), tabu search (TS), and hybrid tabu search algorithms indicates its superiority over others, both in terms of computational time as well as total tardiness reduction

An ESPC algorithm based approach to solve inventory deployment problem

Global competitiveness has enforced the hefty industries to become more customized. To compete in the market they are targeting the customers who want exotic products, and faster and reliable deliveries. Industries are exploring the option of satisfying a portion of their demand by converting strategically placed products, this helps in increasing the variability of product produced by them in short lead time. In this paper, authors have proposed a new hybrid evolutionary algorithm named Endosymbiotic-Psychoclonal (ESPC) algorithm to determine the amount and type of product to stock as a semi product in inventory. In the proposed work the ability of previously proposed Psychoclonal algorithm to exploit the search space has been increased by making antibodies and antigen more cooperative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results obtained, are compared with other evolutionary algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained, and convergence time required to reach the optimal /near optimal value of the solution

A hybrid CFGTSA based approach for scheduling problem: a case study of an automobile industry

In the global competitive world swift, reliable and cost effective production subject to uncertain situations, through an appropriate management of the available resources, has turned out to be the necessity for surviving in the market. This inspired the development of the more efficient and robust methods to counteract the existing complexities prevailing in the market. The present paper proposes a hybrid CFGTSA algorithm inheriting the salient features of GA, TS, SA, and chaotic theory to solve the complex scheduling problems commonly faced by most of the manufacturing industries. The proposed CFGTSA algorithm has been tested on a scheduling problem of an automobile industry, and its efficacy has been shown by comparing the results with GA, SA, TS, GTS, and hybrid TSA algorithms

Optimizing the performance of an integrated process planning and scheduling problem: an AIS-FLC based approach

The present market scenario demands an integration of process planning and scheduling to stay competitive with others. In the present work, an integrated process planning and scheduling model encapsulating the salient features of outsourcing strategy has been proposed. The paper emphasizes on the role of outsourcing strategy in optimizing the performance of enterprises in rapidly changing environment. In the present work authors have proposed an artificial immune system based AIS-FLC algorithm embedded with the fuzzy logic controller to solve the complex problem prevailing under such scenario, while simultaneously optimizing the performance. The authors have shown the efficacy of the proposed algorithm by comparing the results with other random search methods

CLINICAL POTENTIALITY OF DHANVAYAS (FAGONIA CRETICA LINN.) PASTE IN THE MANAGEMENT OF CHRONIC WOUND – A CASE REPORT

Management of chronic wound becomes difficult when it overlays by recurrent infection, peripheral tissue oedema or slough/necrotized tissues. Wound debridement provides healthy environment by removing of unhealthy tissues. In practice of Ayurveda, many of herbs or herbo-mineral formulations are being used for wound care. Dhanvayas, also known as Dhamaso, is an under shrub belongs to Zygophyllaceae family. Traditionally it is being used in fever, hepatitis, boil, skin eruption, tumours and as blood purifier. Animal experimental studies also proves its wound healing properties.Here a case of chronic wound on left lower limb over anterior aspect of the tibia associated with recurrent cellulitis, serous discharge and itching; attended the OPD of Shalya Tantra Department of IPGT&RA, Jamnagar. On measurement it was 8 cm x 4 cm sized. After taking proper history, clinical examination and necessary investigations this case was successfully treated with local application of Dhanvayas (Fagonia cretica Linn.) powder as paste. Wound was daily cleaned with Dhanvayas kwatha (Decoction) and then paste was applied over the lesions in the morning and continued till healing of wound. Assessment was done in regular interval. Itching followed by discharge was reduced remarkably within week. Wound was healed completely within six weeks without any complication which showed wound healing activity of Dhanvayas powder

A Prototype Modelling of Ebers for Video Transmission in Wireless Adhoc Network

Provisioning of video streaming over ad hoc wireless networks exhibits challenges associated with high packet loss rates and are delay sensitive Excessive packet loss can cause significant degradation in quality of video perceived by users of real-time video applications The recent studies suggest that Forward Error Correction FEC is a good technique for decreasing the negative impact of packet loss on video quality in error control scheme This paper introduces an Estimation based Error Reduction Scheme EBERS to support video communication in ad hoc wireless networks The EBERS considers a frame estimation parameter to support varied bandwidths and attain the delay requirements to support video communication It is also responsible for improvising the QoS offered The EBERS considers layered and embodies distortion limiting features owing to which reduced forward error correction is achieved thus obtaining reduced frame errors transmission errors and retransmission of frames Thereby obtaining high degree of quality of service QoS The comparative study conducted proves the efficiency of the EBERS scheme over the existing mechanism

Preface: Swarm Intelligence, Focus on Ant and Particle Swarm Optimization

In the era globalisation the emerging technologies are governing engineering industries to a multifaceted state. The escalating complexity has demanded researchers to find the possible ways of easing the solution of the problems. This has motivated the researchers to grasp ideas from the nature and implant it in the engineering sciences. This way of thinking led to emergence of many biologically inspired algorithms that have proven to be efficient in handling the computationally complex problems with competence such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), etc. Motivated by the capability of the biologically inspired algorithms the present book on ""Swarm Intelligence: Focus on Ant and Particle Swarm Optimization"" aims to present recent developments and applications concerning optimization with swarm intelligence techniques. The papers selected for this book comprise a cross-section of topics that reflect a variety of perspectives and disciplinary backgrounds. In addition to the introduction of new concepts of swarm intelligence, this book also presented some selected representative case studies covering power plant maintenance scheduling; geotechnical engineering; design and machining tolerances; layout problems; manufacturing process plan; job-shop scheduling; structural design; environmental dispatching problems; wireless communication; water distribution systems; multi-plant supply chain; fault diagnosis of airplane engines; and process scheduling. I believe these 27 chapters presented in this book adequately reflect these topics

Artificial Intelligence in Maxillofacial Radiology by Leaps and Bounds

Artificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. AI is capable of mimicking human brain. Recent advances in machine learning have produced algorithms that allow automated and accurate detection, imaging, diagnosis, as well as other specialties of dentistry, which reduces stressful work and manpower. The AI plays a major role in Dental imaging by diagnosing the conditions based on the Radiographic or optical images. AI technology in dentistry could reduce cost, time, human expertise and medical error.AI in everyday life are growing by leaps and bounds. By no means there exists a doubt in the ascendancy of integrating AI into practice

The Role of Natural Laccase Redox Mediators in Simultaneous Dye Decolorization and Power Production in Microbial Fuel Cells

Redox mediators could be used to improve the efficiency of microbial fuel cells (MFCs) by enhancing electron transfer rates and decreasing charge transfer resistance at electrodes. However, many artificial redox mediators are expensive and/or toxic. In this study, laccase enzyme was employed as a biocathode of MFCs in the presence of two natural redox mediators (syringaldehyde (Syr) and acetosyringone (As)), and for comparison, a commonly-used artificial mediator 2,2′-azinobis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) was used to investigate their influence on azo dye decolorization and power production. The redox properties of the mediator-laccase systems were studied by cyclic voltammetry. The presence of ABTS and As increased power density from 54.7 ± 3.5 mW m−2 (control) to 77.2 ± 4.2 mW m−2 and 62.5 ± 3.7 mW m−2 respectively. The power decreased to 23.2 ± 2.1 mW m−2 for laccase with Syr. The cathodic decolorization of Acid orange 7 (AO7) by laccase indicated a 12–16% increase in decolorization efficiency with addition of mediators; and the Laccase-Acetosyringone system was the fastest, with 94% of original dye (100 mgL−1) decolorized within 24 h. Electrochemical analysis to determine the redox properties of the mediators revealed that syringaldehyde did not produce any redox peaks, inferring that it was oxidized by laccase to other products, making it unavailable as a mediator, while acetosyringone and ABTS revealed two redox couples demonstrating the redox mediator properties of these compounds. Thus, acetosyringone served as an efficient natural redox mediator for laccase, aiding in increasing the rate of dye decolorization and power production in MFCs. Taken together, the results suggest that natural laccase redox mediators could have the potential to improve dye decolorization and power density in microbial fue