Browsing by Author "Kulkarni, Girish"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Exact and Heuristic Algorithms for the q-mode Problem
    (2005-05-18) Kulkarni, Girish; Stephen Roberts, Committee Member; Shu-Cherng Fang, Committee Member; Carla Savage, Committee Member; Yahya Fathi, Committee Chair
    In this dissertation we focus on the development of exact and inexact (i.e., heuristic) algorithms for the q-mode problem. The exact algorithms are based on integer programming models for the q-mode problem. We discuss the theoretical properties of an existing IP model and propose several enhancements. We also propose a new IP model for the problem and investigate these models through a comprehensive computational experiment. The experiment reveals that, in practice, the IP models are more effective for instances with strong natural clusters but less effective for instances containing weak natural clusters. We also propose exact algorithms based on the Benders decomposition for one of the IP models. The heuristic algorithm that we propose for the q-mode problem is a local improvement algorithm that is based on a very large scale neighborhood structure. We evaluate the algorithm through a computational experiment and empirically demonstrate its effectiveness.
  • No Thumbnail Available
    A Tabu Search Algorithm for the Steiner Tree Problem.
    (2002-09-04) Kulkarni, Girish; Dr. Yahya Fathi, Committee Chair; Dr Stephen Roberts, Committee Member; Dr. George Rouskas, Committee Member
    The Steiner Tree problem in graphs is an NP-hard problem having applications in many areas including telecommunication, distribution and transportation systems. We survey, briefly, a few exact methods and a few heuristic approaches that have been proposed for solving this problem. Further, we propose a tabu search algorithm whose key feature includes a neighborhood definition consisting of exchange of key paths. The algorithm is empirically tested by running computational experiments on problem sets, with known optimal values, that are available over the internet. The results from the tabu search are compared with the optimal values and with the results of a well-known heuristic procedure. The experimental results show that the tabu search algorithm is reasonably successful. It produces near-optimal solutions in the experiments conducted and performs better than the heuristic procedure. We also explore other avenues for future work and possible extensions to the tabu search algorithm.