Redefining the application of an evolutionary algorithm for the optimal pipe sizing problem

Extensive work has been reported for the optimization of water distribution networks (WDNs) using different optimization techniques. Out of these techniques, evolutionary algorithms (EAs) were found to be more efficient as compared with conventional techniques like linear programming and dynamic programming. Most of the EAs are complex meta-heuristics techniques and need tuning of algorithm-specific parameters. Rao algorithms (Rao-I and Rao-II) do not need any algorithm-specific parameters and hence eliminate the process of sensitivity analysis. In the present work, Rao algorithms are applied for the optimal pipe sizing of WDNs. The optimization results in terms of optimal pipe diameters and the number of evaluations for five different benchmark networks are compared with other EAs. For the two-loop, Hanoi, Go-Yang, and Kadu network, computational efficiency in terms of minimum function evaluations for Rao-I and Rao-II is found to be greater than 78.5 and 83.58%, respectively, when compared with the largest number of minimum function evaluations for other evolutionary techniques. It is seen that Rao algorithms are simple to apply and efficient and do not need any parameter tuning which reduces a large number of computational efforts.

A New Noninterior Continuation Method for Solving a System of Equalities and Inequalities

By using slack variables and minimum function, we first reformulate the system of equalities and inequalities as a system of nonsmooth equations, and, using smoothing technique, we construct the smooth operator. A new noninterior continuation method is proposed to solve the system of smooth equations. It shows that any accumulation point of the iteration sequence generated by our algorithm is a solution of the system of equalities and inequalities. Some numerical experiments show the feasibility and efficiency of the algorithm.

Thresholding Selection Based on Fuzzy Entropy and Bee Colony Algorithm for Image Segmentation

Image thresholding segmentation based on Bee Colony Algorithm (BCA) and fuzzy entropy is presented in this chapter. The fuzzy entropy function is simplified with single parameter. The BCA is applied to search the minimum value of the fuzzy entropy function. According to the minimum function value, the optimal image threshold is obtained. Experimental results are provided to demonstrate the superior performance of the proposed approach.

Perancangan Robot Pengikut Garis Sederhana Sebagai Perangkat Pelatihan Tingkat Pemula

<p>Tulisan ini melaporkan perancangan robot sederhana pengikut garis. Dalam hal ini hasil rancangan akan digunakan sebagai perangkat pelatihan siswa sekolah menengah, sehingga rancangan dibatasi pada fungsi minimumnya agar pembuatan dapat dilakukan secara <em>in house</em>. Perangkat keras dibangun menggunakan photodioda dan LED IR pada sistem sensor, ATMega16 sebagai pengendali utama dan PCB buatan sendiri.</p><p>Design of a simple line follower robot is reported in this paper. In order to meet the needs on training for school student, the design is restricted to have just the minimum function so that the implementation can be done in house. The hardware built utilizes photodiodes and IR LED as sensor system, ATMega16 as main controller and manually made PCB.</p>

THE NATURAL OPERATIONS OF LINGUISTIC LOGIC

A linguistic truth set in which each element is a linguistic truth value is discussed. Ranking linguistic truth values based on Graded Mean Integration Representation method is discussed also. We then give a decreasing linguistic truth set and an increasing linguistic truth set by using the above ranking method, and present a Not function of linguistic truth value combined by the above decreasing linguistic truth set and the increasing linguistic truth set. A minimum function and a maximum function based on representations of linguistic truth values are introduced. In addition, some natural operations of linguistic logic combined by minimum function and maximum function, and Not function are presented. Some properties of our presented natural operations are presented, and are proved. Furthermore, some application examples of linguistic logical statements are discussed finally.