Landscape Encodings Enhance Optimization

Hard combinatorial optimization problems deal with the search for the minimum cost solutions (ground states) of discrete systems under strong constraints. A transformation of state variables may enhance computational tractability. It has been argued that these state encodings are to be chosen invertible to retain the original size of the state space. Here we show how redundant non-invertible encodings enhance optimization by enriching the density of low-energy states. In addition, smooth landscapes may be established on encoded state spaces to guide local search dynamics towards the ground state

The Optimum Communication Spanning Tree Problem : properties, models and algorithms

For a given cost matrix and a given communication requirement matrix, the OCSTP is defined as finding a spanning tree that minimizes the operational cost of the network. OCST can be used to design of more efficient communication and transportation networks, but appear also, as a subproblem, in hub location and sequence alignment problems. This thesis studies several mixed integer linear optimization formulations of the OCSTP and proposes a new one. Then, an efficient Branch & Cut algorithm derived from the Benders decomposition of one of such formulations is used to successfully solve medium-sized instances of the OCSTP. Additionally, two new combinatorial lower bounds, two new heuristic algorithms and a new family of spanning tree neighborhoods based on the Dandelion Code are presented and tested.Postprint (published version

Incorporating Road Networks into Territory Design

Given a set of basic areas, the territory design problem asks to create a predefined number of territories, each containing at least one basic area, such that an objective function is optimized. Desired properties of territories often include a reasonable balance, compact form, contiguity and small average journey times which are usually encoded in the objective function or formulated as constraints. We address the territory design problem by developing graph theoretic models that also consider the underlying road network. The derived graph models enable us to tackle the territory design problem by modifying graph partitioning algorithms and mixed integer programming formulations so that the objective of the planning problem is taken into account. We test and compare the algorithms on several real world instances

Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods

Copyright @ 2010 Elsevier B.V. All rights reserved.In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the channel assignment. Therefore they bear severe drawback, that is, channel assignment cannot work well with the determined multicast tree. In this paper, we integrate them together and solve it by intelligent computational methods. First, we develop a unified framework which consists of the problem formulation, the solution representation, the fitness function, and the channel assignment algorithm. Then, we propose three separate algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and tabu search). These three algorithms aim to search minimum-interference multicast trees which also satisfy the end-to-end delay constraint and optimize the usage of the scarce radio network resource in wireless mesh networks. To achieve this goal, the optimization techniques based on state of the art genetic algorithm and the techniques to control the annealing process and the tabu search procedure are well developed separately. Simulation results show that the proposed three intelligent computational methods based multicast algorithms all achieve better performance in terms of both the total channel conflict and the tree cost than those comparative references.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

Raptorq-Based Multihop File Broadcast Protocol

The objective of this thesis is to describe and implement a RaptorQ broadcast protocol application layer designed for use in a wireless multihop network. The RaptorQ broadcast protocol is a novel application layer broadcast protocol based on RaptorQ forward error correction. This protocol can deliver a file reliably to a large number of nodes in a wireless multihop network even if the links have high loss rates. We use mixed integer programming with power balance constraints to construct broadcast trees that are suitable for implementing the RaptorQ-based broadcast protocol. The resulting broadcast tree facilitates deployment of mechanisms for verifying successful delivery. We use the Qualcomm proprietary RaptorQ software development kit library as well as a Ruby interface to implement the protocol. During execution, each node operates in one of main modes: source, transmitter, or leaf. Each mode has five different phases: STARTUP, FINISHING (Poll), FINISHING (Wait), FINISHING (Extra), and COMPLETED. Three threads are utilized to implement the RaptorQ-based broadcast protocol features. Thread 1 receives messages and passes them to the receive buffer. Thread 2 evaluates the received message, which can be NORM, POLL, MORE, and DONE, and passes the response message to the send buffer. Thread 3 multicasts the content of the send buffer. Results obtained by testing the implementation of the RaptorQ-based broadcast protocol demonstrate that efficient and reliable distribution of files over multihop wireless networks with a high link loss rates is feasible

Study on efficient planning for advanced logistics network model based on robust genetic algorithm

制度:新 ; 報告番号:甲3000号 ; 学位の種類:博士(工学) ; 授与年月日:2010/2/22 ; 早大学位記番号:新525