A risk mitigation framework for construction / asset management of real estate and infrastructure projects

The increasing demand on residential, office, retail, and services buildings as well as hotels and recreation has been encouraging investors from both private and public sectors to develop new communities and cities to meet the mixed demand in one location. These projects are huge in size, include several diversified functions, and are usually implemented over many years. The real estate projects’ master schedules are usually initiated at an early stage of development. The decision to start investing in infrastructure systems, that can ultimately serve fully occupied community or city, is usually taken during the early development stage. This applies to all services such as water, electricity, sewage, telecom, natural gas, roads, urban landscape and cooling and heating. Following the feasibility phase and its generated implementation schedule, the construction of the infrastructure system starts together with a number of real estate projects of different portfolios (retail, residential, commercial,…etc.). The development of the remaining real estate projects continues parallel to customer occupancy of the completed projects. The occurrence of unforeseen risk events, post completing the construction of infrastructure system, may force decision makers to react by relaxing the implementation of the remaining unconstructed projects within their developed communities. This occurs through postponing the unconstructed project and keeping the original feasibility-based sequence of projects unchanged. Decision makers may also change the sequence of implementing their projects where they may prioritize either certain portfolio or location zone above the other, depending on changes in the market demand conditions. The change may adversely impact the original planned profit in the original feasibility. The profit may be generated from either real estate portfolios and/or their serving Infrastructure system. The negative impact may occur due to possible delayed occupancy of the completed real estate projects which in turn reduces the services demand. This finally results in underutilization of the early implemented Infrastructure system. This research aims at developing a dynamic decision support prototype system to quantify impacts of unforeseen risks on the profitability of real estate projects as well as its infrastructure system in the cases of changing projects’ implementation schedules. It is also aimed to support decision makers with scheduled portfolio mix that maximizes their Expected Gross Profit (EGP) of real estate projects and their infrastructure system. The provided schedules can be either based on location zone or portfolio type to meet certain marketing conditions or even to respect certain relations between neighbor projects’ implementation constraints. In order to achieve the research objectives, a Risk Impact Mitigation (RIM) decision support system is developed. RIM consists mainly of four models, Real Estate Scheduling Optimization Model RESOM, Sustainable Landscape Optimization Model SLOM, District Cooling Optimization Model DCOM and Water Simulation Optimization Model WSOM. Integrated with the three Infrastructure specialized models SLOM, DCOM, WSOM, RESOM provides EGP values for individual Infrastructure systems. The three infrastructure models provide the demand profile that relate to a RESOM generated implementation schedule. RESOM then uses these profiles for calculating the profits using the projects’ capital expenditure and financial expenses. The three models included in this research (SLOM, DCOM and WSOM) relate to the urban landscape, district cooling and water systems respectively. RIM is applied on a large scale real estate development in Egypt. The development was subjected to difficult political and financial circumstances that were not forecasted while preparing original feasibility studies. RIM is validated using a questionnaire process. The questionnaire is distributed to 31 experts of different academic and professional background. RIM’s models provided expected results for different real life cases tested by experts as part of the validation process. The validation process indicated that RIM’s results are consistent, in compliance with expected results and is extremely useful and novel in supporting real estate decision makers in mitigating risk impacts on their profits. The validation process also indicated promising benefits and potential need for developed commercial version for future application within the industry

Distributed genetic algorithm implementation by means of Remote Methods Invocation technique – Java RMI

The aim of this work is distributed genetic algorithm implementation (so called islandalgorithm) to accelerate the optimum searching process in space of solutions. The distributedgenetic algorithm has also smaller chances to fall in local optimum. This conception depends onmutual cooperation of the clients who perform separate work of genetic algorithms on localmachines. As a tool for implementation of distributed genetic algorithm, created to produce netapplication Java technology was chosen. In Java technology, there is a technique of remotemethods invocation – Java RMI. By means of invoking remote methods, objects between theclients and the server RMI can be sent.To test the work of genetic algorithm, searching for maximum function of two variables whichpossess a lot of local maxima and can be written by means of mathematical formula was chosen.The work of the whole system depends on existence of the server on which there are registeredremote services (methods) RMI and clients, each one on a separate machine. Each of the clientshas two threads, one of them accomplishes the work of local genetic algorithm whilst the otheraccomplishes the communication with the server. It sends to the server a new best individualwhich was found by the local genetic algorithm and takes the server form with the individuals, leftthere by other clients.To sum up there was created an engine of distributed genetic algorithm which searches themaximum of function and after a not large modification can be used to solve every optimizationproblem

Applications of agent architectures to decision support in distributed simulation and training systems

This work develops the approach and presents the results of a new model for applying intelligent agents to complex distributed interactive simulation for command and control. In the framework of tactical command, control communications, computers and intelligence (C4I), software agents provide a novel approach for efficient decision support and distributed interactive mission training. An agent-based architecture for decision support is designed, implemented and is applied in a distributed interactive simulation to significantly enhance the command and control training during simulated exercises. The architecture is based on monitoring, evaluation, and advice agents, which cooperate to provide alternatives to the dec ision-maker in a time and resource constrained environment. The architecture is implemented and tested within the context of an AWACS Weapons Director trainer tool. The foundation of the work required a wide range of preliminary research topics to be covered, including real-time systems, resource allocation, agent-based computing, decision support systems, and distributed interactive simulations. The major contribution of our work is the construction of a multi-agent architecture and its application to an operational decision support system for command and control interactive simulation. The architectural design for the multi-agent system was drafted in the first stage of the work. In the next stage rules of engagement, objective and cost functions were determined in the AWACS (Airforce command and control) decision support domain. Finally, the multi-agent architecture was implemented and evaluated inside a distributed interactive simulation test-bed for AWACS Vv\u27Ds. The evaluation process combined individual and team use of the decision support system to improve the performance results of WD trainees. The decision support system is designed and implemented a distributed architecture for performance-oriented management of software agents. The approach provides new agent interaction protocols and utilizes agent performance monitoring and remote synchronization mechanisms. This multi-agent architecture enables direct and indirect agent communication as well as dynamic hierarchical agent coordination. Inter-agent communications use predefined interfaces, protocols, and open channels with specified ontology and semantics. Services can be requested and responses with results received over such communication modes. Both traditional (functional) parameters and nonfunctional (e.g. QoS, deadline, etc.) requirements and captured in service requests

The Management of Manufacturing-Oriented Informatics Systems Using Efficient and Flexible Architectures

Industry and in particular the manufacturing-oriented sector has always been researched and innovated as a result of technological progress, diversification and differentiation among consumers' demands. A company that provides to its customers products matching perfectly their demands at competitive prices has a great advantage over its competitors. Manufacturing-oriented information systems are becoming more flexible and configurable and they require integration with the entire organization. This can be done using efficient software architectures that will allow the coexistence between commercial solutions and open source components while sharing computing resources organized in grid infrastructures and under the governance of powerful management tools.Manufacturing-Oriented Informatics Systems, Open Source, Software Architectures, Grid Computing, Web-Based Management Systems

The Software Continuum Concept: Towards a Biologically Inspired Model for Robust E-Business Software Automation

This paper introduces a new concept, the software continuum concept based on the observation that exists a general parallelism between the software continuum from bits to business/Internet ecosystems and the natural continuum from particles to ecosystems. The general parallelism suggests that homeomorphisms may be identified and therefore some concepts, processes, and/or mechanisms in one continuum can be investigated for application in the other continuum. We argue that the homeomorphisms give rise to a biologically-inspired architectural framework for addressing robust control, robust intelligence, and robust autonomy issues in e-business software and other business-IT integration challenges. As application, we examine the mapping of a major enterprise-level architecture framework to the biologically-inspired framework. Design considerations for robust intelligence and autonomy in large-scale software automation and some major systemic features for flexible business-IT integration are also discussed

Development of an online collaborative working environment for design and manufacturing

This research is to develop a novel collaborative working environment (CWE) for manufacturing and design using advanced Web/Internet technologies such as Web Service, Grid Service and other related software tools/packages. To achieve the above, the following research modules are developed by the author: A service oriented framework for computer aid design, which acts as an online collaboration system, has been developed with the utilisation of the latest technology, Web Service. The concept of Service-Oriented Architecture has been implemented in the framework. Users from anywhere in the world can join the design process from their PCs, no matter what operation system they are using. The service-oriented system has the capability of going through firewalls and can afford multi-users due to the characteristics of Web service. Also the loose-coupling structure makes the system very easy to be updated. Another module for the CWE is to solve the software sharing problem when the platform is used among several geographically dispersed users or organisations. A software package bank system has been developed, which utilised the ideology of service oriented approach and successfully solved traditional problems in this field. Based on the outcomes mentioned above, the research finally developed a more powerful infrastructure using Grid service, which is a further development of Grid computing and Web service. The Grid service is considered to be the most important future solvent for Internet

A Web-based flood forecasting system for Shuangpai region

Author name used in this publication: K. W. ChauAuthor name used in this publication: Chun-Tian Cheng2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Fairness Categorization Policy Of Queuing Theory For Geographic Information System Job Scheduling

Geographic Information System (GIS) is a compute-intensive plus data-intensive application that deals with substantial amount of spatial data processing and rendering of three-dimensional (3D) images of the locations. Besides research work on data or image processing part of GIS applications, scheduling of GIS workload can be further studied to improve the performance of GIS applications. In this regards, this thesis proposes an algorithm of job scheduler named Fair Categorized Queue Scheduling (FCQS) which distributes jobs of GIS applications efficiently. Queuing theory is applied in FCQS for job scheduling processes meanwhile the GIS job arrivals are distributed according to Poisson distribution. Each category of jobs is served along with First-Come First-Served (FCFS) basic using the Multiple Queues Multiple Machines (MQMM) configuration. The experiment through simulation has been carried out to evaluate the performance of FCQS and other queue configurations such as Single Queue Single / Multiple Machine(s) (SQSM / SQMM) and Multiple Queues Single / Multiple Machines(s) (MQSM / MQMM). The results proved that the FCQS algorithm achieved the highest throughput with 24 jobs or 72.727% more than the lowest throughput of SQSM. Additionally, the total Input / Output (IO) transferring time can be reduced up to 49.194% by using multiple jobs processing compared to single job processing within small jobs, attaining lower average turnaround time and waiting time simultaneously. Last but not least, the optimization of grid resources has been significantly improved by decreasing total pending jobs to 28.261% instead of the highest 52.174%