MERGING OPTIMALITY CONDITIONS WITH GENETIC ALGORITHM OPERATORS TO SOLVE SINGLE MACHINE TOTAL WEIGHTED TARDINESS PROBLEM

1.Introduction Production sequencing and scheduling is one of the most important activities in production planning and control.Sequencing is defined as the order in which the jobs are processed through the machines.The allocation of machines over time to process a collection of jobs is defined as Scheduling.Several methods have been developed to solve the scheduling problem which can be classified as follows:1)efficient optimal methods,2)implicit and explicit,or complete enumerative methods,a…     

Operationalising “Double-Loop” Learning in Service Organisations: A Systems Approach for Creating Knowledge

Learning organisation literature has widely discussed the connections between “double-loop” learning and its significance to organisational performance, but paying little attention to tools and systems that can operationalise “double-loop” learning in organisations. This paper investigates the impact of applying a systems approach for service operations design, expressed as the Vanguard Method (Seddon, Freedom from command and control: a better way to make the work work, 2003), in order to activate “double-loop” learning in service organisations. Two case studies were conducted in the banking mortgage operations and adults’ social care services in the UK, using the dimensions of the learning organisation questionnaire (DLOQ), semi-structured interviews, observations, and documents. The findings of the cross-case analysis support the link of applying the Vanguard Method with operationalising “double-loop” learning through three main factors, namely systematic-operations improvement, organisational capacity development, and outside-in mode of work; that are all embedded into the seven dimensions of the DLOQ. The value of this paper is the introduction of a service operations design tool that can activate “double-loop” learning performance in the fast changing knowledge era. It also provides an impetus for service organisations to creatively influence employees’ competencies to effectively improve internal systems.     

Integrating complex system dynamics of pandemic influenza with a multi-criteria decision making model for evaluating public health strategies

Recent developments in computational sciences and computer modeling have allowed emergency preparedness exercises to include simulation models as supporting tools.These simulation models are generally built for predicting temporal and geographic patterns of disease spread.However sole use of simulation models in exercise design falls short in terms of incorporating policy decision makers’ preferences into decision-making processes.In this paper,a general framework for exercising public health preparedness plans with a decision support system is presented to integrate estimation of key epidemiological parameters with a system dynamics model of an outbreak.A multi-criteria decision making framework,an Analytical Hierarchy Process model,is then developed and integrated with the simulation model to help public health policy makers prioritize their response goals and evaluate mitigation strategies in a table-top exercise environment.     

Selection Optimal Drill Rigs by Grey Relational Analysis Method

Based upon the main properties of the relational analysis in grey system theory,a newmethod to select optimal drill rigs is proposed in this paper.Under the unified technique economicindex,with the practical data of four kinds of drill rigs in the mining district,east of Sichuan,China,an optimal reference number series was constructed.Through calculating the relational grade     

The stability of a complex social system

Analyzing communication data within a social structure represented by a wholesale agricultural market demonstrates the utility of network analysis techniques for identifying systems. A representation of these data in matrix form permits exploration of the stability properties of the system. The stability analyses lend some support for theoretical arguments pertaining to the conditions leading to system equilibrium.     

The systems approach to economic modeling in India

This paper reviews the evolutionary changes that have taken place in the systems approach to macroeconomic modeling of the Indian economy over the last 40 years in general and the last 5 years in particular. Considering the fact that the systems approach has been used both at the official level, for planning purposes, and at the academic level, as inputs to the planning process, the paper covers both these aspects in a thematic manner. Commencing from the initial official efforts, with their emphasis on aggregate consistency models, through the intermediate phases of developing programming and nonoptimizing systems and, finally, to the current academic interest in control and chaotic systems, this evolution is considered primarily against the backdrop of the changing perspectives of systems theorists and designers.     

Modeling and forecasting of stock markets under a system adaptation framework

This paper adopts the concept of dynamic feedback systems to model the behavior of financial markets,or more specifically,the stock market from a dynamic system point of view.Based on a feedback adaptation scheme,the authors model the movement of a stock market index within a framework that is composed of an internal dynamic model and an adaptive filter.The output-error model is adopted as the internal model whereas the adaptive filter is a time-varying state space model with instrumental variables.Its input-output behavior,and internal as well as external forces are then identified.Special attention has also been paid to the recent financial crisis by examining the movement of Dow Jones Industrial Average(DJIA) as an example to illustrate the advantage of the proposed framework.Supported by time-varying causality tests,five influential factors from economic and sentiment aspects are introduced as the input of this framework.Testing results show that the proposed framework has a much better prediction performance than the existing methods,especially in complicated economic situations.An application of this framework is also presented with focuses on forecasting the turning periods of the market trend.Realizing that a market trend is about to change when the external force begins to exhibit clear patterns in its frequency responses,the authors develop a set of rules to recognize this kind of clear patterns.These rules work well for stock indexes from US, China and Singapore.     

Growth of Magnetite Nanoparticles under Magnetic Fields

1 Introduction Over the past several years, the preparation and characterization ofnanoscale magnetic materials, especially one-dimensional (1D) nanostructure, have attracted much attention as the nanomaterials would allow investigating the fundamental aspects of magnetic-ordering phenomena in magnetic materials with reduced dimensions and could lead to new potential applications such as data storage technology[1-6].