A Technique for Optimal Sequential Maintenance Scheduling

This paper presents the mathematical development of, and a simple solution technique for, an optimal sequential maintenance scheduling problem. The model is shown to satisfy the Kuhn-Tucker conditions, the necessary and sufficient conditions for the existence of an optimal solution. Real-world systems consisting of mixtures of constant and increasing failure rate devices are considered in the model. Sequential preventive maintenance schedules are developed for groups of identical items with increasing failure rates. Provision is made for the corrective maintenance of these groups if failures occur in between the preventive maintenance schedules. Also, constant failure rate devices are accorded corrective maintenance when failures occur. Optimality is achieved by minimizing the total annual maintenance cost, subject to constraints on the system availability, number of maintenance personnel and intervals of preventive maintenance. The model is applied to a coal mine power system example.     

Hybrid BWO-IACO Algorithm for Cluster Based Routing in Wireless Sensor Networks

Wireless Sensor Network (WSN) comprises a massive number of arbitrarily placed sensor nodes that are linked wirelessly to monitor the physical parameters from the target region. As the nodes in WSN operate on inbuilt batteries, the energy depletion occurs after certain rounds of operation and thereby results in reduced network lifetime. To enhance energy efficiency and network longevity, clustering and routing techniques are commonly employed in WSN. This paper presents a novel black widow optimization (BWO) with improved ant colony optimization (IACO) algorithm (BWO-IACO) for cluster based routing in WSN. The proposed BWO-IACO algorithm involves BWO based clustering process to elect an optimal set of cluster heads (CHs). The BWO algorithm derives a fitness function (FF) using five input parameters like residual energy (RE), inter-cluster distance, intra-cluster distance, node degree (ND), and node centrality. In addition, IACO based routing process is involved for route selection in inter-cluster communication. The IACO algorithm incorporates the concepts of traditional ACO algorithm with krill herd algorithm (KHA). The IACO algorithm utilizes the energy factor to elect an optimal set of routes to BS in the network. The integration of BWO based clustering and IACO based routing techniques considerably helps to improve energy efficiency and network lifetime. The presented BWO-IACO algorithm has been simulated using MATLAB and the results are examined under varying aspects. A wide range of comparative analysis makes sure the betterment of the BWO-IACO algorithm over all the other compared techniques.     

Convenient and efficient syntheses of 4-hydroxy-2(E)-nonenal and 4-oxo-2(E)-nonenal

Lipid peroxidation products 4-hydroxy-2(E)-nonenal (HNE) and 4-oxo-2(E)-nonenal (ONE) were conveniently synthesized using Wittig and Horner-Wardsworth-Emmons (HWE) reaction. Wittig or HWE reaction between an easily prepared phosphorane or phosphonate with glyoxal dimethyl acetal gave a protected 4-oxo-2(E)-nonenal. Hydrolysis gave 4-oxo-2(E)-nonenal, whereas reduction followed by hydrolysis gave 4-hydroxy-2(E)-nonenal.