Bidding Strategy to Support Decision-Making Based on Comprehensive Information in Construction Projects

© 2016 Ru Liang et al. This paper develops a unified method to support contractor for bidding selection in construction projects. A cross-functional contractor with 28 candidate units distributed in the three departments (construction units, design units, and suppliers) is used as an example. This problem is first formulated as a 0-1 quadratic programming problem through optimizing individual performance and collaborative performance of the candidate units based on individual information and collaborative information. Then, a multiobjective evolutionary algorithm is designed to solve this problem and a bidding selection problem for a major bridge project is used to demonstrate our proposed method. The results show that the decision-maker (DM) obtains a better contractor if he pays more attention to collaborative performance

Are conventions solutions ? Contrasting visions of the relationship between convention and uncertainty

This paper maps out different conceptions and dynamic accounts of convention developed within game theory, Post Keynesian economics and the économie des conventions. These accounts are distinguished in terms of the way in which they conceive of uncertainty (as probabilistic or radical).

Nuclear Power

The world of the twenty first century is an energy consuming society. Due to increasing population and living standards, each year the world requires more energy and new efficient systems for delivering it. Furthermore, the new systems must be inherently safe and environmentally benign. These realities of today's world are among the reasons that lead to serious interest in deploying nuclear power as a sustainable energy source. Today's nuclear reactors are safe and highly efficient energy systems that offer electricity and a multitude of co-generation energy products ranging from potable water to heat for industrial applications. The goal of the book is to show the current state-of-the-art in the covered technical areas as well as to demonstrate how general engineering principles and methods can be applied to nuclear power systems

A RISK-INFORMED DECISION-MAKING METHODOLOGY TO IMPROVE LIQUID ROCKET ENGINE PROGRAM TRADEOFFS

This work provides a risk-informed decision-making methodology to improve liquid rocket engine program tradeoffs with the conflicting areas of concern affordability, reliability, and initial operational capability (IOC) by taking into account psychological and economic theories in combination with reliability engineering. Technical program risks are associated with the number of predicted failures of the test-analyze-and-fix (TAAF) cycle that is based on the maturity of the engine components. Financial and schedule program risks are associated with the epistemic uncertainty of the models that determine the measures of effectiveness in the three areas of concern. The affordability and IOC models' inputs reflect non-technical and technical factors such as team experience, design scope, technology readiness level, and manufacturing readiness level. The reliability model introduces the Reliability- As-an-Independent-Variable (RAIV) strategy that aggregates fictitious or actual hotfire tests of testing profiles that differ from the actual mission profile to estimate the system reliability. The main RAIV strategy inputs are the physical or functional architecture of the system, the principal test plan strategy, a stated reliability-bycredibility requirement, and the failure mechanisms that define the reliable life of the system components. The results of the RAIV strategy, which are the number of hardware sets and number of hot-fire tests, are used as inputs to the affordability and the IOC models. Satisficing within each tradeoff is attained by maximizing the weighted sum of the normalized areas of concern subject to constraints that are based on the decision-maker's targets and uncertainty about the affordability, reliability, and IOC using genetic algorithms. In the planning stage of an engine program, the decision variables of the genetic algorithm correspond to fictitious hot-fire tests that include TAAF cycle failures. In the program execution stage, the RAIV strategy is used as reliability growth planning, tracking, and projection model. The main contributions of this work are the development of a comprehensible and consistent risk-informed tradeoff framework, the RAIV strategy that links affordability and reliability, a strategy to define an industry or government standard or guideline for liquid rocket engine hot-fire test plans, and an alternative to the U.S. Crow/AMSAA reliability growth model applying the RAIV strategy

Models for the optical dispersion relations of amorphous semiconductors

The development of empirical expressions for the spectral dependence of the real and imaginary components of the dielectric function have proven useful over the years. These expressions can be applied in the analysis of optical data, including the interpretation of transmittance, reflectance, and ellipsometric spectra obtained from thin film semiconductors. Also, they can be used in performance simulations of optoelectronic devices, such as solar cells. In this thesis, a critical comparison of a number of empirical models for the real and imaginary components of the dielectric function is performed. A number of crystalline and disordered semiconductors of interest are considered in this analysis. Also, a new means of numerically evaluating the real component of the dielectric function from the imaginary component is developed based on a Kramers-Kronig relation. Applications of this approach are discussed