Ken-ichi Tokoro

An efficient hybrid genetic algorithm for a fixed channel assignment problem with limited bandwidth

We need an efficient channel assignment algorithm for increasing channel re-usability, reducing call-blocking rate and reducing interference in any cellular systems with limited bandwidth and a large number of subscribers. We propose an efficient hybrid genetic algorithm for a fixed channel assignment problem with limited bandwidth constraint. The proposed GA finds a good sequence of codes for a virtual machine that produces channel assignment. Results are given which show that our GA produces far better solutions to several practical problems than existing GAs.

Real-Coded Parameter-Free Genetic Algorithm for Job-Shop Scheduling Problems

We propose a new genetic algorithm (GA) for job-shop scheduling problems (JSSP) based on the parameter-free GA (PfGA) and parallel distributed PfGA proposed by Sawai et al. The PfGA is not only simple and robust, but also does not need to set almost any genetic parameters in advance that need to be set in other GAs. The performance of PfGA is high for functional optimization problems of 5- or 10-dimensions, but its performance for combinatorial optimization problems, which search space is larger than the functional optimization, has not been investigated. We propose a new algorithm for JSSP based on an extended PfGA, extended to real-coded version. The GA uses random keys for representing permutation of jobs. Simulation results show that the proposed GA can attain high quality solutions for typical benchmark problems without parameter tuning.

A Parameter-Free Genetic Algorithm for a Fixed Channel Assignment Problem with Limited Bandwidth

Increasing the channel re-usability is necessary for reducing the call-blocking rate in any cellular systems with limited bandwidth and a large number of subscribers. To increase the re-usability, we need an efficient channel assignment algorithm that minimizes the sum of blocking cost and interference cost. We propose a new genetic algorithm for the problem based on the parameter-free GA. The proposed GA finds a good sequence of codes for a virtual machine that produces channel assignment. Results are given which show that our GA, without tedious parameter tuning, produces far better solutions to several practical problems than the existing GAs.

Performance evaluation of a parameter-free genetic algorithm for job-shop scheduling problems

The job-shop scheduling problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Genetic Algorithms (GAs) for solving the JSSP have been proposed, and they perform well compared with other approaches [1].

Empirical Performance Evaluation of a Parameter-Free GA for JSSP

The job-shop scheduling problem (JSSP) is a well known di.cult NP-hard problem. Genetic Algorithms (GAs) for solving the JSSP have been proposed, and they perform well compared with other approaches [1]. However, the tuning of genetic parameters has to be performed by trial and error. To address this problem, Sawai et al. have proposed the Parameter-free GA (PfGA), for which no control parameters for genetic operation need to be set in advance [3].

Development of Management Support System for Gas Turbine Hot Gas Path Parts

The combined cycle power plants operating in Japan are normally provided with two or more gas turbines and spare parts in quantities as required by the number of gas turbine units in operation. Since the quantity of hot gas path parts installed in a gas turbine is massive, the parts required for a gas turbine are arranged in groups so as to simplify the control of parts inventory. These parts groups are replaced and repaired at each inspection. Furthermore, since the costs of hot gas path parts are very high, using the parts efficiently and implementing measuring to prolong the life of the parts are very important. Detailed parts rotation schedules are prepared to properly rotate the spare parts groups. In doing so, the length of service life, quantity of spare parts, schedules for using the parts for several years to come, and time required for maintenance and repairs must be taken into consideration. Special characteristics of respective power plants such as plans for prolonging the service life of parts and various costs must be taken into consideration. Since it is difficult to prepare the schedules for rotating parts automatically, skilled workers are carrying out most of work manually at present. Against such a backdrop, the authors have developed the “Management Support System for Gas Turbine Hot Gas Path Parts”. This system can be used to reduce the maintenance and repair costs by optimizing parts rotation schedules. The basic concepts of the development are as follows. 1) Some parts can be shared among plural number of power plants with the gas turbines of the same model. A user freely sets models of the gas turbines, categorization of parts, and numbers of the parts dealt with. 2) The unit of the part management is done based on not groups but serial numbers. Moreover, replacing parts is enabled. 3) The program is modulated according to the functions. Addition, change, and deletion of these functions are facilitated. The total system is developed platform-free.Copyright