Metastrategy Simulated annealing and tabu search for combinatorial optimization problems

SIGLEAvailable from British Library Document Supply Centre-DSC:DX196316 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

I-MEET Framework for the Evaluation eGovernment Services from Engaging Stakeholders' Perspectives

NoI-MEET is an Integrated Model for Evaluating E-government services Transformation from stakeholders' perspectives. It is based on an integration of concepts from value chain management and business process transformation to optimize the system-wide value chain of providers and users simultaneously. It aims to align stakeholders on a common global value against traditional disintegrated approaches where each stakeholder optimizes its e-service local value at the expense of others. The measured variables are derived from the literature and focused groups. They are then categorized into cost and risk (Inputs) and (benefit and opportunity) Outputs after a validation process based on Structured Equation Models using a sample of 1540 user-responses of e-services in the UK. Finally, Data Envelopment Analysis is conducted to derive an aggregated of an e-service satisfaction value using the various inputs and outputs. The empirical results demonstrate that data-derived weights for aggregating indicators are variable rather than fixed across e-services. The novelty of the assessment approach lies in its capability to provide informed suggestions to set targets to improve an eservice from the perspective of all engaging users. Hence it provides a better transformation of public administration services and improved take up by citizens and businesses

A probabilistic analysis of local search

We present a theoretical average-case analysis of a 2-opt algorithm for the traveling salesman problem. First, we give a model which allows us to compute the required number of steps and the distribution of final solutions found by a best improvement algorithm. This model is empirically validated for a restricted version of the 2-opt neighborhood. Secondly, we present a semi-empirical analysis of the average-case performance of an iterated 2-opt and Lin-Kernighan algorithm based on empirically obtained parameters

Preface

Peer reviewed: YesNRC publication: Ye