Masaaki Minagawa

A Genetic Approach to the Line Balancing Problem

Abstract This paper describes an approach to the line balancing problem: an well known combinatorial problem. The approach method aims at improving dependency of the conventional heuristic methods on targeted problem domain. The method starts with rough estimation of solution and improves it through a GA based search process. The work element assignments are encoded to strings and,to find near-optimal solutions, manipulated by standard genetic operators. Some experiments are carried out and applicability of the proposed methodology is shown.

A Packing Problem of Many Circles into Rectangles. A New Approach by Vibration Control Method.

This paper describes a new approach to solve a problem of packing circles into a given rectangular area. In our problem setting, we assume that the circles have different diameters and the number of circles is above one hundred. Starting from random allocation of circles in relatively large rectangular area, by giving external force, we vibrate the circles and obtain more dense allocation. Elasticity is assumed in resulting forces by collision between the circles. The circles will continue to collide with each other while changing their positions continually. While the circles being vibrated, the rectangular area will be shrunk to minimize resulting waste. Final positions of the circles and the size of the rectangle will be determined when the circles cease to move. To obtain effective vibration to move the circles, we give the vibration according to Lissajouss figures and we tune the parameters of the figures using Genetic Algorithms. Magnitudes of amplitude, frequency and phase of the figures are encoded as artificial chromosomes and manipulated by conventional genetic operators. In the paper, we carry out some simulation basis experiments, and examine the applicability of the proposed methodology.

A Study on Autonomic Machines in the Vibrating Potential Field. An Approach to Job-Shop Scheduling Problem.

The job-shop scheduling problem is a well-known planning problem. The solution should incorporate production control. This paper aims at developing a new scheduling system based on the decentralized management approach to describing a mathematical model of the autonomic machines. Here, in order to develop a more generalized theory for the control of autonomic machines, the vibrating potential method (VPM) is introduced. The VPM is characterized by placement of each units potential function on its own harmonic wave as an axis. Each unit receives potential energy from the vibrating potential field (VPF) by convolution and determines its own strategy of motion independently. This paper proposes a new control method to be used in the field and discusses its application to the job-shop scheduling problem.

Expert rule acquisition and refinement by GA-an approach to multidimensional problems

Describes a genetic algorithm (GA) based approach to realize expert knowledge acquisition and refinement in a real world problem: parameter value determination for metal shaft grinding where several trade-offs exist among operational conditions to obtain expected surface finish. Causal relations are encoded to strings in (condition): (action) form and implemented as a rule based system. Genetic operators are applied to: (1) discretization of continuous parameter values; and (2) refinement of rules.<<ETX>>