modified shuffled frog leaping algorithm

Several industrial products such as moulds, dies, engine block, automotive parts, etc., require machining of a large number of holes. Similarly, applications like boiler plates, food-business processing separator's, printed circuit boards, drum and trammel screens, etc., consist of a matrix of a large number of holes. Many machining operations, such as drilling, enlargement, tapping, or reaming, are needed to achieve the final sizes of individual holes, resulting in a variety of possible sequences to complete the hole-making operations. The major issue involved in hole-making operations is the tool travel time. It is often vital to determine the optimal sequence of operations so that the overall processing cost of hole-making operations can be minimized. In this work, thus an attempt is made to minimize the total tool travel of hole-making operations by using a relatively new optimization algorithm known as modified shuffled frog leaping for the determination of the optimal sequence of operations. Modification is made in the present shuffled frog-leaping algorithm by using three parameters with their positive values in order to widen the search capability of the existing algorithm. This paper considers three case studies of a rectangular matrix of holes to explain the proposed procedure. The outcomes of optimization with a modified shuffled frog-leaping algorithm are compared to those obtained with the genetic algorithm and the ant colony algorithm. Additionally, the higher dimensional problem of 20 x 20 rectangular matrix of holes is considered in this work.

Restructuring the recent developments in the power system and problems arising from construction as well as the maintenance of large power plants lead to increase in using the Distributed Generation (DG) resources. DG units due to its specifications, technology and location network connectivity can improve system and load point reliability indices. In this paper, the allocation and sizing of distributed generators in distribution electricity networks are determined through using an optimization method. The objective function of the proposed method is based on improving the reliability indices, such as a System Average Interruption Duration Index (SAIDI), and Average Energy Not Supplied (AENS) per customer index at the lowest cost. The optimization is based on the Modified Shuffled Frog Leaping Algorithm (MSFLA) aiming at determining the optimal DG allocation and sizing in the distribution network. The MSFLA is a new mimetic meta-heuristic algorithm with efficient mathematical function and global search capability. To evaluate the proposed algorithm, the 34-bus IEEE test system is used. In addition, the finding of comparative studies indicates the better capability of the proposed method compared with the genetic algorithm in finding the optimal sizing and location of DG’s with respect to the used objective function.