205099619
Simulated annealing and genetic algorithms for scheduling products with multi-level product structure
We consider a short-term production scheduling problem in a manufacturing system producing products with multi-level product structure, and their components and subassemblies. The problem is to schedule production of components, subassemblies, and final products with the objective of minimizing the weighted sum of tardiness and earliness of the items. We consider due dates of final products, precedence relationships among items, and processing capacity of the manufacturing system. The scheduling problem is solved with simulated annealing and genetic algorithms, which are search heuristics often used for global optimization in a complex search space. To compare the performance of these algorithms with the finite loading method, which is often used in practice, computational experiments are carried out using randomly generated test problems and results are reported.
21112002
A backward approach in list scheduling algorithms for multi-machine tardiness problems
Abstract List scheduling algorithms are commonly used for multi-machine scheduling problems, especially for those with precedence relationships among operations. In most list scheduling algorithms, operations are scheduled forward. In this paper, we suggest a backward approach in which the operations are scheduled backward. We discuss some details that must be considered when applying the backward approach to problems with due dates and suggest several methods of defining parameters needed in the backward approach. Performance of this approach is tested on job shop problems and identical machine problems with several types of precedence constaints.
44579377
Head Detection and Tracking for the Car Occupant's Pose Recognition
This paper describes a Vision-based Occupant Pose Recognition (VOPR) system, which can ensure a safe airbag deployment. Head detection and its tracking are necessary for occupant’s pose recognition in the car, since the position of occupant’s head provides valuable information, such as his pose, size, position, and so on. We use the stereo cameras to extract a disparity map. Against variable lighting conditions including the night drive, we adopt infrared illumination as well as normal one. Results suggest that VOPR system is reliable and performs reasonably well.
206667073
Fault-diagnosis for a class of distributed control multistage interconnection networks
A class of (2 log/sub 2/ N-1)-stage interconnection networks is suitable for fault-tolerance with effective use of the redundant paths which provide multiple disjoint paths between each pair of input/output terminals. This paper focuses on a new fault-diagnosis method for a class of distributed control (2 log/sub 2/ N-1)-stage interconnection networks. To perform this fault-diagnosis method, the self-routing tags based on a given multistage interconnection network are generated for each phase. Six tests with self-routing tags can detect a faulty switching element and a link stuck fault in a (2 log/sub 2/ N-1)-stage interconnection network. Regarding the fault location problem, the fault-location procedure to use O(log/sub 2/ log 2N) tests for a distributed control network is proposed.
344302
New topologies for genetic search space
We propose three distance measures for genetic search space. One is a distance measure in the population space that is useful for understanding the working mechanism of genetic algorithms. Another is a distance measure in the solution space for K-grouping problems. This can be used for normalization in crossover. The third is a level distance measure for genetic algorithms, which is useful for measuring problem difficulty with respect to genetic algorithms. We show that the proposed measures are metrics and the measures are efficiently computed.
7564297
Problem-Independent Schema Synthesis for Genetic Algorithms
As a preprocessing for genetic algorithms, static reordering helps genetic algorithms effectively create and preserve high-quality schemata, and consequently improves the performance of genetic algorithms. In this paper, we propose a static reordering method independent of problem-specific knowledge. One of the novel features of our reordering method is that it is applicable to any problem with no information about the problem. The proposed method constructs a weighted complete graph from the gene distances calculated from solutions with relatively high fitnesses, transforms them into a gene-interaction graph, and finds a gene rearrangement. Extensive experimental results showed significant improvement for a number of applications.
40331728
Efficient 2-D Convolution Algorithm with the Single-Data Multiple Kernel Approach
Abstract A fast implementation of convolution operation is described. The implementation takes advantage of various properties of commonly used kernels. First, the kernel elements are analyzed and rearranged, grouping the kernel elements of the same absolute value together and arranging trivial multiplication cases separately. Then the sequence of computing convolution sums is modified so that all the kernel elements could be multiplied by the same data element at each step. This new algorithm significantly reduces the number of multiplication operations for most widely used kernels. Our experiment shows that the performance improvement of two to seven over the direct implementation is achievable for most kernels. The required overhead (extra memory and preprocessing) is proportional to the kernel size and is negligible.