Bat Algorithm for Multi-objective Optimisation

Engineering optimization is typically multiobjective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimization algorithms. Recently, Xin-She Yang proposed a bat-inspired algorithm for solving nonlinear, global optimisation problems. In this paper, we extend this algorithm to solve multiobjective optimisation problems. The proposed multiobjective bat algorithm (MOBA) is first validated against a subset of test functions, and then applied to solve multiobjective design problems such as welded beam design. Simulation results suggest that the proposed algorithm works efficiently.Comment: 12 pages. arXiv admin note: text overlap with arXiv:1004.417

Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm

The main aim of this paper is to solve a path planning problem for an autonomous mobile robot in static and dynamic environments. The problem is solved by determining the collision-free path that satisfies the chosen criteria for shortest distance and path smoothness. The proposed path planning algorithm mimics the real world by adding the actual size of the mobile robot to that of the obstacles and formulating the problem as a moving point in the free-space. The proposed algorithm consists of three modules. The first module forms an optimized path by conducting a hybridized Particle Swarm Optimization-Modified Frequency Bat (PSO-MFB) algorithm that minimizes distance and follows path smoothness criteria. The second module detects any infeasible points generated by the proposed hybrid PSO-MFB Algorithm by a novel Local Search (LS) algorithm integrated with the hybrid PSO-MFB algorithm to be converted into feasible solutions. The third module features obstacle detection and avoidance (ODA), which is triggered when the mobile robot detects obstacles within its sensing region, allowing it to avoid collision with obstacles. The simulation results indicate that this method generates an optimal feasible path even in complex dynamic environments and thus overcomes the shortcomings of conventional approaches such as grid methods. Moreover, compared to recent path planning techniques, simulation results show that the proposed hybrid PSO-MFB algorithm is highly competitive in terms of path optimality

Daily monitoring of TeV gamma-ray emission from Mrk 421, Mrk 501, and the Crab Nebula with HAWC

We present results from daily monitoring of gamma rays in the energy range $\sim0.5$ to $\sim100$ TeV with the first 17 months of data from the High Altitude Water Cherenkov (HAWC) Observatory. Its wide field of view of 2 steradians and duty cycle of $>95$% are unique features compared to other TeV observatories that allow us to observe every source that transits over HAWC for up to $\sim6$ hours each sidereal day. This regular sampling yields unprecedented light curves from unbiased measurements that are independent of seasons or weather conditions. For the Crab Nebula as a reference source we find no variability in the TeV band. Our main focus is the study of the TeV blazars Markarian (Mrk) 421 and Mrk 501. A spectral fit for Mrk 421 yields a power law index $\Gamma=2.21 \pm0.14_{\mathrm{stat}}\pm0.20_{\mathrm{sys}}$ and an exponential cut-off $E_0=5.4 \pm 1.1_{\mathrm{stat}}\pm 1.0_{\mathrm{sys}}$ TeV. For Mrk 501, we find an index $\Gamma=1.60\pm 0.30_{\mathrm{stat}} \pm 0.20_{\mathrm{sys}}$ and exponential cut-off $E_0=5.7\pm 1.6_{\mathrm{stat}} \pm 1.0_{\mathrm{sys}}$ TeV. The light curves for both sources show clear variability and a Bayesian analysis is applied to identify changes between flux states. The highest per-transit fluxes observed from Mrk 421 exceed the Crab Nebula flux by a factor of approximately five. For Mrk 501, several transits show fluxes in excess of three times the Crab Nebula flux. In a comparison to lower energy gamma-ray and X-ray monitoring data with comparable sampling we cannot identify clear counterparts for the most significant flaring features observed by HAWC.Comment: 18 pages, 10 figures, accepted for publication in The Astrophysical Journa

Bat Algorithm: Literature Review and Applications

Bat algorithm (BA) is a bio-inspired algorithm developed by Yang in 2010 and BA has been found to be very efficient. As a result, the literature has expanded significantly in the last 3 years. This paper provides a timely review of the bat algorithm and its new variants. A wide range of diverse applications and case studies are also reviewed and summarized briefly here. Further research topics are also discussed.Comment: 10 page

The orienting mouse: An input device with attitude

This paper presents a modified computer mouse, the Orienting Mouse, which delivers orientation as an additional dimension of input; when the mouse is moved on a flat surface it reports, in addition to the conventional x, y translation, angular rotation of the device in the x, y plane. The orienting mouse preserves important properties of the standard mouse; all measurements are relative and movement is tracked only while the mouse is on its flat surface. If the user lets go of the mouse, leaving it on the surface, its position and orientation do not change until it is touched again. Picking the mouse up and putting it down in a different orientation leaves the angle and position unchanged. While the concept of sensing mouse rotation is not new, our work focuses on movement and navigation in 3D, rather than on precision positioning tasks. We describe a number of sample applications developed to test its effectiveness in this context. Specific features exploited and described include (i) an algorithm for calculating the mouse angle which cancels drift between the two sensors, and (ii) the use of angular gearing which avoids unnatural and uncomfortable hand positions when moving through large angles; informal user testing validates this idea