The impact of planning delays and other holding costs on housing affordability

Housing affordability is gaining increasing prominence in the Australian socioeconomic landscape, despite strong economic growth and prosperity. It is a major consideration for any new development. However, it is multi-dimensional, has many facets, is complex and interwoven. One factor widely held to impact housing affordability is holding costs. Although it is only one contributor, the nature and extent of its impact requires clarification. It is certainly more multifarious than simple calculation of the interest or opportunity cost of land holding. For example, preliminary analysis suggests that even small shifts in the regulatory assessment period can significantly affect housing affordability. Other costs associated with “holding” also impact housing affordability, however these costs cannot always be easily identified. Nevertheless it can be said that ultimately the real impact is felt by those whom can least afford it - new home buyers whom can be relatively easily pushed into the realms of un-affordability.

Initial steps in optimal planning of a distribution system

This paper reports the initial steps of research on planning of rural networks for MV and LV. In this paper, two different cases are studied. In the first case, 100 loads are distributed uniformly on a 100 km transmission line in a distribution network and in the second case, the load structure become closer to the rural situation. In case 2, 21 loads are located in a distribution system so that their distance is increasing, distance between load 1 and 2 is 3 km, between 2 and 3 is 6 km, etc). These two models to some extent represent the distribution system in urban and rural areas, respectively. The objective function for the design of the optimal system consists of three main parts: cost of transformers, and MV and LV conductors. The bus voltage is expressed as a constraint and should be maintained within a standard level, rising or falling by no more than 5%.

Transaction Cost Analysis of PPP Risk Share

PPP (Public Private Partnerships) is a new operation mode of infrastructure projects, which usually undergo long periods and have various kinds of risks in technology, market, politics, policy, finance, society, natural conditions and cooperation. So the government and the private agency should establish the risk-sharing mechanism to ensure the successful implementation of the project. As an important branch of the new institutional economics, transaction cost economics and its analysis method have been proved to be beneficial to the proper allocation of risks between the two parts in PPP projects and the improvement of operation efficiency of PPP risk-sharing mechanism. This paper analyzed the transaction cost of the projects risk-sharing method and the both risk carriers. It pointed out that the risk-sharing method of PPP projects not only reflected the spirit of cooperation between public sector and private agency, but also minimized the total transaction cost of the risk sharing mechanism itself. Meanwhile, the risk takers had to strike a balance between the beforehand cost and the afterwards cost so as to control the cost of risk management. The paper finally suggested three ways which might be useful to reduce the transaction cost: to choose appropriate type of contract of PPP risk-sharing mechanism, to prevent information asymmetry and to establish mutual trust between the two participants.

Holding cost model for Greenfield Housing developments

Presentation provided to a PhD Colloquium between two Australian and one Malaysian University providing the opportunity to inform and critique progress of students concerning their selected topic. This presentation essentially involves "The conceptualisation, sensitivity and measurement of holding costs and other selected elements impacting housing affordability" as provided by Gary Owen Garner of QUT, with research objectives thus: 1. To establish the nature and composition of holding costs over time, as related to residential property in Australia, and internationally. 2. To examine the linkages that may exist between various planning instruments, the length of regulatory assessment periods, and housing affordability. 3. To develop a model that quantifies the impact of holding costs on housing affordability in Australia, with a particular focus on the consequences of extended assessment periods as a component of holding costs. Thus, provide clarification as to the impact of holding costs on overall housing affordability.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

Solar powered UAV for fire prevention and planning

This project aims to develop a methodology for designing and conducting a systems engineering analysis to build and fly continuously, day and night, propelled uniquely by solar energy for one week with a 0.25Kg payload consuming 0.5 watt without fuel or pollution. An airplane able to fly autonomously for many days could find many applications. Including coastal or border surveillance, atmospherical and weather research and prediction, environmental, forestry, agricultural, and oceanic monitoring, imaging for the media and real-estate industries, etc. Additional advantages of solar airplanes are their low cost and the simplicity with which they can be launched. For example, in the case of potential forest fire risks during a warm and dry period, swarms of solar airplanes, easily launched with the hand, could efficiently monitor a large surface, reporting rapidly any fire starts. This would allow a fast intervention and thus reduce the cost of such disaster, in terms of human and material losses. At higher dimension, solar HALE platforms are expected to play a major role as communication relays and could replace advantageously satellites in a near future.

Responding to sustainability challenge and cost implications in highway construction projects

Highway construction often requires a significant capital input; therefore it often causes serious financial implications for developers, owners and operators. The recent industry-wide focus on sustainability has added a new dimension to the evaluation of highway projects, particularly on the economical scale of ‘going green’. Comprehensive analysis of the whole-of-life highway development that responds to sustainability challenges is one of the primary concerns for stakeholders. Principles of engineering economics and life cycle costing have been used to determine the incremental capacity investments for highway projects. However, the consideration of costs and issues associated with sustainability is still very limited in current studies on highway projects. Previous studies have identified that highway project investments are primarily concerned with direct market costs that can be quantified through life cycle costing analysis (LCCA). But they tend to ignore costs that are difficult to calculate, as those related to environmental and social elements. On a more positive note, these studies proved that the inclusion of such costs is an essential part of the overall development investment and a primary concern for decision making by the stakeholders. This paper discusses a research attempt to identify and categorise sustainability cost elements for highway projects. Through questionnaire survey, a set of sustainability cost elements on highway projects has been proposed. These cost elements are incorporated into the extension of some of the existing Life Cycle Costing Analysis (LCCA) models in order to produce a holistic financial picture of the highway project. It is expected that a new LCCA model will be established to serve as a suitable tool for decision making for highway project stakeholders.

Constraints to cost effective land supply

The ready availability of suitably zoned and serviced land is one of the key factors in the timely and cost effective provision of new land for development. Unfortunately, in many high population growth areas, land that may be available does not have ready access to infrastructure, or the appropriate designation/s (zoning) in place. The corresponding lag in supply frequently bears the blame for the resultant disequilibrium in the market and affordability pressures on the end product. Government has the capacity to respond to the issue of land supply in a number of ways. Proactive measures define longer term goals and set the ground rules moving forwards. Reactive policy decisions are made in an often hostile environment where stakeholder interests conflict. With a trend to increased regulation, government risks further constraining the viability of land development in high growth areas, without full consideration of all the supply side variables. This preliminary paper will identify a number of the variables which may be constraining the supply of land for residential development in South East Queensland given the current regulatory environment. It will examine the interrelationship between these supply side constraints, a full understanding of which is required by government in order for its policies to stimulate, rather than restrict the supply of land in this high growth region.

UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser

This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

Optimal mission path planning (MPP) for an air sampling unmanned aerial system

This paper presents advanced optimization techniques for Mission Path Planning (MPP) of a UAS fitted with a spore trap to detect and monitor spores and plant pathogens. The UAV MPP aims to optimise the mission path planning search and monitoring of spores and plant pathogens that may allow the agricultural sector to be more competitive and more reliable. The UAV will be fitted with an air sampling or spore trap to detect and monitor spores and plant pathogens in remote areas not accessible to current stationary monitor methods. The optimal paths are computed using a Multi-Objective Evolutionary Algorithms (MOEAs). Two types of multi-objective optimisers are compared; the MOEA Non-dominated Sorting Genetic Algorithms II (NSGA-II) and Hybrid Game are implemented to produce a set of optimal collision-free trajectories in three-dimensional environment. The trajectories on a three-dimension terrain, which are generated off-line, are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different position with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of coupling a Hybrid-Game strategy to a MOEA for MPP tasks. The reduction of numerical cost is an important point as the faster the algorithm converges the better the algorithms is for an off-line design and for future on-line decisions of the UAV.

UAS Mission Path Planning System, (MPPS) using hybrid-game coupled to multi-objective optimizer

This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

Implementing value management as a decision-making tool in the design stages of design and build construction projects : a methodology for improved cost optimization

Value Management (VM) has been proven to provide a structured framework, together with other supporting tools and techniques, that facilitate effective decision-making in many types of projects, thus achieving ‘best value’ for clients. One of the major success factors of VM in achieving better project objectives for clients is through the provision of beneficial input by multi-disciplinary team members being involved in critical decision-making discussions during the early stage of construction projects. This paper describes a doctoral research proposal based on the application of VM in design and build construction projects, especially focusing on the design stage. The research aims to study the effects of implementing VM in design and build construction projects, in particular how well the methodology addresses issues related to cost overruns resulting from poor coordination and overlooking of critical constructability issues amongst team members in construction projects in Malaysia. It is proposed that through contractors’ early involvement during the design stage, combined with the use of the VM methodology, particularly as a decision-making tool, better optimization of construction cost can be achieved, thus promoting more efficient and effective constructability. The main methods used in this research involve a thorough literature study, semi-structured interviews, and a survey of major stakeholders, a detailed case study and a VM workshop and focus group discussions involving construction professionals in order to explore and possibly develop a framework and a specific methodology for the facilitating successful application of VM within design and build construction projects.

The importance of environmental issues and costs in Life Cycle Cost Analysis (LCCA) for highway projects

Sustainability has been increasingly recognised as an integral part of highway infrastructure development. In practice however, the fact that financial return is still a project’s top priority for many, environmental aspects tend to be overlooked or considered as a burden, as they add to project costs. Sustainability and its implications have a far-reaching effect on each project over time. Therefore, with highway infrastructure’s long-term life span and huge capital demand, the consideration of environmental cost/ benefit issues is more crucial in life-cycle cost analysis (LCCA). To date, there is little in existing literature studies on viable estimation methods for environmental costs. This situation presents the potential for focused studies on environmental costs and issues in the context of life-cycle cost analysis. This paper discusses a research project which aims to integrate the environmental cost elements and issues into a conceptual framework for life cycle costing analysis for highway projects. Cost elements and issues concerning the environment were first identified through literature. Through questionnaires, these environmental cost elements will be validated by practitioners before their consolidation into the extension of existing and worked models of life-cycle costing analysis (LCCA). A holistic decision support framework is being developed to assist highway infrastructure stakeholders to evaluate their investment decision. This will generate financial returns while maximising environmental benefits and sustainability outcome.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.