Showing papers by "Indian Institute of Management Calcutta published in 1988"
01 Jun 1988
TL;DR: It is shown in this paper that Mero’s algorithm (B′) is not as good as claimed and this method of modifiable heuristics can in general reduce the total number of node expansions.
Abstract: Most of the previous studies in heuristic search have assumed that the heuristic estimate of a node remains constant during the execution of algorithms In a recent study, L. Mero suggested a method for run-time modification of heuristic estimate of nodes. This method of modifiable heuristics can in general reduce the total number of node expansions. It is shown in this paper, with counter examples, that Mero’s algorithm (B′) is not as good as claimed.
11 citations
Proceedings Article•
21 Aug 1988
TL;DR: A new best-first search algorithm for the CRGKP is described, where the heuristic estimate function is monotone, and optimal solutions are guaranteed.
Abstract: The Constrained Rectangular Guillotine Knapsack Problem (CRGKP) is a variant of the two-dimensional cutting stock problem. In the CRGKP, a stock rectangle of dimensions (L,W) is given. There are n different types of demanded rectangles, with the ith type ri having length 1i, width wi, value vi and demand constraint bi. S must be cut using only orthogonal guillotine cuts to produce ai copies of ri, 1 ≤ i ≤ n, so as to maximize alvl + a2v2 +....+ anvn, subject to the constraints ai ≤ bi, l ≤ i ≤ n. All parameters are integers. Here a new best-first search algorithm for the CRGKP is described. The heuristic estimate function is monotone, and optimal solutions are guaranteed. Computational results indicate that this method is superior in performance to the two existing algorithms for the problem.
10 citations
01 Jul 1988
TL;DR: In this paper, Chakraborty compared the two theories and sketches the similarities and differences between them and found that Guna theory is more comprehensive in its scope than Transactional Analysis, and is therefore able to explain better, both the industry's impact on environment, and the aggravated negative tendencies in our society.
Abstract: A good theory of social interaction is fundamental to individual, organizational and societal well-being and progress. Transactional Analysis, the psychology of human relationships, is such a theory that is immensely popular in management literature. Guna Dynamics is an Indian psycho-philosophical theory of human conduct and behaviour that has retained its logical appeal over thousands of years. Yet, rigorous study and application of Guna theory to management is grossly neglected. S K Chakraborty compares the two theories and sketches the similarities and differences between them. He finds that Guna theory is more comprehensive in its scope than Transactional Analysis, and is, therefore, able to explain better, both the industry's impact on environment, and the aggravated negative tendencies in our society. He proposes a synthesis of the two theories for more effective handling of human-relationships.
9 citations
01 Jun 1988
TL;DR: It is shown that, for most probability distributions on the heuristic estimates, E(Z) is exponential in N; the one major exception being the case when the number of goal nodes is polynomial in N and the normalizing function for the error is logarithmic.
Abstract: A search graph has the form of an m-ary tree with bi-directional arcs of unit cost. There is a goal node at a distance N from the root, and there may be other goal nodes at distances ≥ N from the root. It is assumed that the heuristic estimates of nongoal nodes, after being appropriately normalized, are independent and identically distributed random variables. The heuristic is not required to be admissible. Under what conditions is the expected number of node expansions E(Z) polynomial in N? Earlier efforts by Pearl and others at answering this question have considered search trees with only one goal node. An attempt is made here to develop a general and unified method of analysis applicable to situations with more than one goal node. It is shown that, for most probability distributions on the heuristic estimates, E(Z) is exponential in N; the one major exception being the case when the number of goal nodes is polynomial in N and the normalizing function for the error is logarithmic. Pearl’s contention that the average-case analysis of weighted heuristic search is not too attractive is also verified. It is hoped that the general approach described here will encourage similar studies on search graphs other than trees.
8 citations