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This paper aims to identify the optimum level of factors or parameters that affect the energy absorption of conoidal structures by grey relational examination. To optimize crashworthiness parameters of conical structures, the L9 orthogonal array has been adopted to design the experiments. The tailor-made thin-walled conical structures were fabricated by three most important factors, such as base diameter, height, and thickness, as design variables, and they were subjected to axial compression in a quasi-static method. The important responses of crashworthiness indicators such as the mean crushing force and specific energy absorption (SEA) were calculated with the help of a load-displacement curve. Experimental results showed that the crushing behaviours of conical structures were fairly significant. Grey relational analysis (GRA) and analysis of variance are used toobtain the optimal levels of parameters. From the results, the optimum levels of parameters are found to be a base diameter of 180 mm, a height of 120 mm, and a thickness of 1.5 mm.

We aim to suggest a simple genetic algorithm (GA) and other four hybrid GAs (HGAs) for solving the asymmetric distance-constrained vehicle routing problem (ADVRP), a variant of vehicle routing problem (VRP). The VRP is a difficult NP-hard optimization problem that has numerous real-life applications. The VRP aims to find an optimal tour that has least total distance (or cost) to provide service to n customers (or nodes or cities) utilizing m vehicles so that every vehicle starts journey from and ends journey at a depot (headquarters) and visits every customer only once. The problem has many variations, and we consider the ADVRP for this study, where distance traveled by every vehicle must not exceed a predefined maximum distance. The proposed GA uses random initial population followed by sequential constructive crossover and swap mutation. The HGAs enhance the initial solution using 2-opt search method and incorporate a local search technique along with an immigration procedure to obtain effective solution to the ADVRP. Experiments have been conducted among the suggested GAs by solving several restricted and unrestricted ADVRP instances on asymmetric TSPLIB utilizing several vehicles. Our experiments claim that the suggested HGAs using local search methods are very effective. Finally, we reported a comparative study between our best HGA and a state-of-the-art algorithm on asymmetric capacitated VRP and found that our algorithm is better than the state-of-the-art algorithm for the instances.

This study examines viscoelastic fractional nanofluid flow through Darcy medium. Memory characteristics due to elasticity are explored with noninteger time derivatives. The unsteady motion of MHD flow is modeled by nonlinear differential equations. Buoyancy forces are incorporated via convection parameters in the flow domain. Fractional relaxation time is considered to control the propagation speed of temperature. A finite difference, along with finite element, a numerical algorithm has been developed for the computation of governing flow equations. Friction coefficient, Sherwood numbers, and Nusselt numbers are computed for the noninteger derivative model. Simulations revealed that noninteger numbers have congruous behavior for concentration, temperature, and velocity fields. It is also noted that heat flux, δ 1 , and mass flux, δ 2 , numbers have contradictory effects on the friction coefficient. Various flows, particularly in polymer industries and electrospinning for the production of nanofibers, can be tackled in a comparable pattern.

The multiple travelling salesman problem (MTSP), an extension of the well-known travelling salesman problem (TSP), is studied here. In MTSP, starting from a depot, multiple salesmen require to visit all cities so that each city is required to be visited only once by one salesman only. It is NP-hard and is more complex than the usual TSP. So, exact optimal solutions can be obtained for smaller sized problem instances only. For large-sized problem instances, it is essential to apply heuristic algorithms, and amongst them, genetic algorithm is identified to be successfully deal with such complex optimization problems. So, we propose a hybrid genetic algorithm (HGA) that uses sequential constructive crossover, a local search approach along with an immigration technique to find high-quality solution to the MTSP. Then our proposed HGA is compared against some state-of-the-art algorithms by solving some TSPLIB symmetric instances of several sizes with various number of salesmen. Our experimental investigation demonstrates that the HGA is one of the best algorithms.

The facility layout problem (FLP) is a very important class of NP-hard problems in operations research that deals with the optimal assignment of facilities to minimize transportation costs. The quadratic assignment problem (QAP) can model the FLP effectively. One of the FLPs is the hospital facility layout problem that aims to place comprehensive clinics, laboratories, and radiology units within predefined boundaries in a way that minimizes the cost of movement of patients and healthcare personnel. We are going to develop a hybrid method based on discrete differential evolution (DDE) algorithm for solving the QAP. In the existing DDE algorithms, certain issues such as premature convergence, stagnation, and exploitation mechanism have not been properly addressed. In this study, we first aim to discover the issues that make the current problem worse and to identify the best solution to the problem, and then we propose to develop a hybrid algorithm (HDDETS) by combining the DDE and tabu search (TS) algorithms to enhance the exploitation mechanism in the DDE algorithm. Then, the performance of the proposed HDDETS algorithm is evaluated by implementing on the benchmark instances from the QAPLIB website and by comparing with DDE and TS algorithms on the benchmark instances. It is found that the HDDETS algorithm has better performance than both the DDE and TS algorithms where the HDDETS has obtained 42 optimal and best-known solutions from 56 instances, while the DDE and TS algorithms have obtained 15 and 18 optimal and best-known solutions out of 56 instances, respectively. Finally, we propose to apply the proposed algorithm to find the optimal distributions of the advisory clinics inside the Azadi Hospital in Iraq that minimizes the total travel distance for patients when they move among these clinics. Our application shows that the proposed algorithm could find the best distribution of the hospital’s rooms, which are modeled as a QAP, with reduced total distance traveled by the patients.

A 3 × 3 factorial experiment was conducted on Labeo rohita fingerlings to evaluate the effect of dietary oxidized oil and vitamin E. Nine experimental diets were made, based on three degrees of oil oxidation (fresh oil, low oil oxidation and high oil oxidation), and each level of oxidation was further supplemented with three levels of vitamin E (0, 100 and 1,000 mg/kg). Weight gain% and specific growth rate (SGR) of fish fed fresh fish oil and low oil oxidation level were significantly higher than highly oxidized oil. Moreover, vitamin E supplemented fish also showed better growth performance. Oil oxidation caused a significant reduction in the concentrations of α‐tocopherol and increase in TBARS level and antioxidant enzyme activities in fish liver and muscles. However, increasing the dietary vitamin E abrogated these effects. Dietary vitamin E supplementation improved the fatty acid, more specifically polyunsaturated fatty acids profile of oxidized oil fed fish. In conclusion, dietary oxidized fish oil increased the oxidative stress condition of fish but supplementation of high dose of vitamin E prevented lipid oxidation, improved growth performance and fatty acid profile of L. rohita.

Recent research has shown that carbon nanotube (CNT) acts as a model reinforcement material for fabricating nanocomposites. The addition of CNT as a reinforcing material into the matrix improves the mechanical, thermal, tribological, and electrical properties. In this research paper multiwalled carbon nanotube (MWCNT), with different weight percentage (5%, 10%, and 15%), was reinforced into manganese dioxide (MnO2) matrix using solution method. The different weight % of MWCNT/MnO2 nanocomposite powders was compacted and then sintered. The phase analysis, morphology, and chemical composition of the nanocomposites were examined by X-ray diffractometer, Field Emission Scanning Electron Microscope (FESEM), and Energy Dispersive X-Ray (EDX), respectively. The XRD analysis indicates the formation of MWCNT/MnO2 nanocomposites. The FESEM surface morphology analysis shows that MnO2 nanotube is densely grown on the surface of MWCNT. Further, microhardness of MWCNT/MnO2 nanocomposite was measured and it was found that 10 wt% has higher microhardness in comparison to 5 and 15 wt%. The microhardness of the composites is influenced by mass density, nanotube weight fraction, arrangement of tubes, and dispersion of MWCNT in H2SO4(aq) solution.

Summary Effective phasor measurement unit (PMU) placement is a key to the implementation of efficient and economically feasible wide area measurement systems in modern power systems. This paper proposes a pragmatic approach for cost-effective stage-wise deployment of PMUs while considering realistic constraints. Inspired from a real world experience, the proposed approach optimally allocates PMU placement in a stage-wise manner. The proposed approach also considers large-scale wind integration for effective grid state monitoring of wind generation dynamics. The proposed approach is implemented on the Danish power system projected for the year 2040. Furthermore, practical experience learnt from an optimal PMU placement project aimed at PMU placement in the Danish power system is presented, which is expected to provide insight of practical challenges at ground level that could be considered by PMU placement software developers as well as for future research in this field. Copyright © 2016 John Wiley & Sons, Ltd.

A simple lexisearch algorithm that uses path representation method for the asymmetric traveling salesman problem (ATSP) is proposed, along with an illustrative example, to obtain exact optimal solution to the problem. Then a data-guided lexisearch algorithm is presented. First, the cost matrix of the problem is transposed depending on the variance of rows and columns, and then the simple lexisearch algorithm is applied. It is shown that this minor preprocessing of the data before the simple lexisearch algorithm is applied improves the computational time substantially. The efficiency of our algorithms to the problem against two existing algorithms has been examined for some TSPLIB and random instances of various sizes. The results show remarkably better performance of our algorithms, especially our data-guided algorithm.