40835687
Partitioning trees of supply and demand
Assume that a tree T has a number ns of "supply vertices" and all the other vertices are "demand vertices." Each supply vertex is assigned a positive number called a supply, while each demand vertex is assigned a positive number called a demand. One wishes to partition T into exactly ns subtrees by deleting edges from T so that each subtree contains exactly one supply vertex whose supply is no less than the sum of demands of all demand vertices in the subtree. The "partition problem" is a decision problem to ask whether T has such a partition. The "maximum partition problem" is an optimization version of the partition problem. In this paper, we give three algorithms for the problems. The first is a linear-time algorithm for the partition problem. The second is a pseudo-polynomial-time algorithm for the maximum partition problem. The third is a fully polynomial-time approximation scheme (FPTAS) for the maximum partition problem.
32325022
Algorithms for Finding Distance-Edge-Colorings of Graphs
For a bounded integer l, we wish to color all edges of a graph G so that any two edges within distance l have different colors. Such a coloring is called a distance-edge-coloring or an l-edge-coloring of G. The distance-edge-coloring problem is to compute the minimum number of colors required for a distance-edge-coloring of a given graph G. A partial k-tree is a graph with tree-width bounded by a fixed constant k. We first present a polynomial-time exact algorithm to solve the problem for partial k-trees, and then give a polynomial-time 2-approximation algorithm for planar graphs.
2226240
Partitioning Trees of Supply and Demand
Assume that a tree T has a number ns of "supply vertices" and all the other vertices are "demand vertices." Each supply vertex is assigned a positive number called a supply, while each demand vertex is assigned a positive number called a demand. One wish to partition T into exactly ns subtrees by deleting edges from T so that each subtree contains exactly one supply vertex whose supply is no less than the sum of demands of all demand vertices in the subtree. The "partition problem" is a decision problem to ask whether T has such a partition. The "maximum partition problem" is an optimization version of the partition problem. In this paper, we give three algorithms for the problems. First is a linear-time algorithm for the partition problem. Second is a pseudo-polynomial-time algorithm for the maximum partition problem. Third is a fully polynomial-time approximation scheme (FPTAS) for the maximum partition problem.
10045838
Algorithms for finding distance-edge-colorings of graphs
For a bounded integer @?, we wish to color all edges of a graph G so that any two edges within distance @? have different colors. Such a coloring is called a distance-edge-coloring or an @?-edge-coloring of G. The distance-edge-coloring problem is to compute the minimum number of colors required for a distance-edge-coloring of a given graph G. A partial k-tree is a graph with tree-width bounded by a fixed constant k. We first present a polynomial-time exact algorithm to solve the problem for partial k-trees, and then give a polynomial-time 2-approximation algorithm for planar graphs.
21650131
On a web browsing support system with 3d visualization
Existing commercial Web browsers provide various utilities and functions, e.g., Web bookmarks and a browsing history list. Since the bookmark and history functions only the title and URL of the Web page, users who cannot remember the contents of each Web page have difficulty retracing their steps. In this paper, we propose a bookmark system based on a 3D interface. Additionally, our system offers three main functions a 3D browsing history function, a marker function, and a look-ahead loading function. These functions enable users to browse Web pages more effectively.
18603528
A Qualitative-Quantitative Methods-Based e-Learning Support System in Economic Education
This paper describes a new qualitative-quantitative simulator to help buyers learn how to make decisions when they purchase goods. In this paper, we propose an e-learning support system (LSDM) for assisting user decision making by applying artificial intelligence technology. When buyers purchase expensive items, they must carefully select these items from many alternatives. The learning support system provides useful information that assists consumers in purchasing goods. We employ qualitative simulations because the output simulation results are useful. Our system consists of a qualitative processing system and a quantitative calculation system. When users use the system, they first input information on the goods they want to purchase. The information input by users is used in the qualitative simulation. Next, they supply the details of their budgets, the rate of loans, and several other factors, on a form. The system then integrates the results of simulation and the user's input data and proposes plans to aid in their decision process. The system has several advantages: it can be used by simple input, the process of simulation is easy to understand, users can learn how to make decisions by trial and error, and the users can base their decision making on synthetic results.
15889327
Towards Better Approximation of Winner Determination for Combinatorial Auctions with Large Number of Bids
We propose new approximate algorithms for combinatorial auctions with massively large number of (more than 100,000) bids. In this paper, we focus on a more practical approximated algorithm in the context of revenue maximization. We propose a hill-climbing greedy algorithm, a SA-like random search algorithm, and their enhancement for searching multiple key parameter values. The experimental results demonstrate that our algorithms perform approximately 0.997 optimality compared with the optimal solutions and better than previously presented approximated algorithms. We also demonstrate that our algorithms are a kind of anytime algorithm that bring better results in shorter computational time that can be applied to large and dynamic electronic markets.
2241033
Multiple negotiations among agents for a distributed meeting scheduler
We present a method for multi-agent negotiation for implementing a distributed meeting scheduler. In the meeting scheduler, an agent negotiates with other agents about making a public schedule by referring user's private schedules and preferences. We propose a new persuasion method for multi-agent negotiation for reflecting private preferences. We call the method multiple negotiations. In order to reach a consensus effectively, we propose an effective preference revision mechanism based on the multi attribute utility theory. We have implemented a distributed meeting scheduler to show how effectively the multiple negotiations can be used. The result shows that the multiple negotiations are effective in supporting group decision-making for scheduling a meeting.
40274616
On the spectra of certain distance-regular graphs
Let r be an undirected graph whose vertex-set V(F) is the set (ZJ~ , u2 ,..., v,>. The adjacency matrix of I’ is the n x n matrix A = A(r), over the complex number field, whose entries aij are given by a,j = 1 if vi and vi are adjacent, = 0 otherwise. DEFINITION 1. The spectrum of r is the set of distinct eigenvalues 4l , 4 ,**-> Od of A(F), together with their multiplicities, written m(&), m(4),..., m(0,). Since r is undirected, A is symmetric, and so the Bi are all real numbers. We arrange the Bi in increasing order, namely, 0, < O1 < *.. < e dMany studies have been done on the spectra of graphs by many mathematicians. Some of them may be found, for instance, in Biggs [2].