Hybrid-Game Strategies for multi-objective design optimization in engineering

A number of Game Strategies (GS) have been developed in past decades. They have been used in the fields of economics, engineering, computer science and biology due to their efficiency in solving design optimization problems. In addition, research in multi-objective (MO) and multidisciplinary design optimization (MDO) has focused on developing robust and efficient optimization methods to produce a set of high quality solutions with low computational cost. In this paper, two optimization techniques are considered; the first optimization method uses multi-fidelity hierarchical Pareto optimality. The second optimization method uses the combination of two Game Strategies; Nash-equilibrium and Pareto optimality. The paper shows how Game Strategies can be hybridised and coupled to Multi-Objective Evolutionary Algorithms (MOEA) to accelerate convergence speed and to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid-Game Strategies are clearly demonstrated

Bounded parameter Markov Decision Processes with average reward criterion

Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP). Unlike the case of an MDP, the notion of an optimal policy for a BMDP is not entirely straightforward. We consider two notions of optimality based on optimistic and pessimistic criteria. These have been analyzed for discounted BMDPs. Here we provide results for average reward BMDPs. We establish a fundamental relationship between the discounted and the average reward problems, prove the existence of Blackwell optimal policies and, for both notions of optimality, derive algorithms that converge to the optimal value function.

Adaptive online gradient descent

We study the rates of growth of the regret in online convex optimization. First, we show that a simple extension of the algorithm of Hazan et al eliminates the need for a priori knowledge of the lower bound on the second derivatives of the observed functions. We then provide an algorithm, Adaptive Online Gradient Descent, which interpolates between the results of Zinkevich for linear functions and of Hazan et al for strongly convex functions, achieving intermediate rates between [square root T] and [log T]. Furthermore, we show strong optimality of the algorithm. Finally, we provide an extension of our results to general norms.

Efficient hybrid-game strategies coupled to evolutionary algorithms for robust multidisciplinary design optimization in aerospace engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.

Multi-objective design optimization of morphing UAV aerofoil/wing using hybridised MOGA

The paper investigates two advanced Computational Intelligence Systems (CIS) for a morphing Unmanned Aerial Vehicle (UAV) aerofoil/wing shape design optimisation. The first CIS uses Genetic Algorithm (GA) and the second CIS uses Hybridized GA (HGA) with the concept of Nash-Equilibrium to speed up the optimisation process. During the optimisation, Nash-Game will act as a pre-conditioner. Both CISs; GA and HGA, are based on Pareto optimality and they are coupled to Euler based Computational Fluid Dynamic (CFD) analyser and one type of Computer Aided Design (CAD) system during the optimisation.

Scheduling techniques to optimise rail operations

In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. The sugarcane transport system is very complex and uses daily schedules, consisting of a set of locomotives runs, to satisfy the requirements of the mill and harvesters. The total cost of sugarcane transport operations is very high; over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. Efficient schedules for sugarcane transport can reduce the cost and limit the negative effects that this system can have on the raw sugar production system. There are several benefits to formulating the train scheduling problem as a blocking parallel-machine job shop scheduling (BPMJSS) problem, namely to prevent two trains passing in one section at the same time; to keep the train activities (operations) in sequence during each run (trip) by applying precedence constraints; to pass the trains on one section in the correct order (priorities of passing trains) by applying disjunctive constraints; and, to ease passing trains by solving rail conflicts by applying blocking constraints and Parallel Machine Scheduling. Therefore, the sugarcane rail operations are formulated as BPMJSS problem. A mixed integer programming and constraint programming approaches are used to describe the BPMJSS problem. The model is solved by the integration of constraint programming, mixed integer programming and search techniques. The optimality performance is tested by Optimization Programming Language (OPL) and CPLEX software on small and large size instances based on specific criteria. A real life problem is used to verify and validate the approach. Constructive heuristics and new metaheuristics including simulated annealing and tabu search are proposed to solve this complex and NP-hard scheduling problem and produce a more efficient scheduling system. Innovative hybrid and hyper metaheuristic techniques are developed and coded using C# language to improve the solutions quality and CPU time. Hybrid techniques depend on integrating heuristic and metaheuristic techniques consecutively, while hyper techniques are the complete integration between different metaheuristic techniques, heuristic techniques, or both.

The neglected dimension of community liveability : impact on social connectedness and active ageing in higher density accommodation

Purpose This thesis is about liveability, place and ageing in the high density urban landscape of Brisbane, Australia. As with other major developed cities around the globe, Brisbane has adopted policies to increase urban residential densities to meet the main liveability and sustainability aim of decreasing car dependence and therefore pollution, as well as to minimise the loss of greenfield areas and habitats to developers. This objective hinges on urban neighbourhoods/communities being liveable places, which residents do not have to leave for everyday living. Community/neighbourhood liveability is an essential ingredient in healthy ageing in place and has a substantial impact upon the safety, independence and well-being of older adults. It is generally accepted that ageing in place is optimal for both older people and the state. The optimality of ageing in place generally assumes that there is a particular quality to environments or standard of liveability in which people successfully age in place. The aim of this thesis was to examine if there are particular environmental qualities or aspects of liveability that test optimality and to better understand the key liveability factors that contribute to successful ageing in place. Method A strength of this thesis is that it draws on two separate studies to address the research question of what makes high density liveable for older people. In Chapter 3, the two methods are identified and differentiated as Method 1 (used in Paper 1) and Method 2 (used in Papers 2, 3, 4 and 5). Method 1 involved qualitative interviews with 24 inner city high density Brisbane residents. The major strength of this thesis is the innovative methodology outlined in the thesis as Method 2. Method 2 involved a case study approach employing qualitative and quantitative methods. Qualitative data was collected using semi-structured, in-depth interviews and time-use diaries completed by participants during the week of tracking. The quantitative data was gathered using Global Positioning Systems for tracking and Geographical Information Systems for mapping and analysis of participants’ activities. The combination of quantitative and qualitative analysis captured both participants’ subjective perceptions of their neighbourhoods and their patterns of movement. This enhanced understanding of how neighbourhoods and communities function and of the various liveability dimensions that contribute to active ageing and ageing in place for older people living in high density environments. Both studies’ participants were inner-city high density residents of Brisbane. The study based on Method 1 drew on a wider age demographic than the study based on Method 2. Findings The five papers presented in this thesis by publication indicate a complex inter-relationship of the factors that make a place liveable. The first three papers identify what is comparable and different between the physical and social factors of high density communities/neighbourhoods. The last two papers explore relationships between social engagement and broader community variables such as infrastructure and the physical built environments that are risk or protective factors relevant to community liveability, active ageing and ageing in place in high density. The research highlights the importance of creating and/or maintaining a barrier-free environment and liveable community for ageing adults. Together, the papers promote liveability, social engagement and active ageing in high density neighbourhoods by identifying factors that constitute liveability and strategies that foster active ageing and ageing in place, social connections and well-being. Recommendations There is a strong need to offer more support for active ageing and ageing in place. While the data analyses of this research provide insight into the lived experience of high density residents, further research is warranted. Further qualitative and quantitative research is needed to explore in more depth, the urban experience and opinions of older people living in urban environments. In particular, more empirical research and theory-building is needed in order to expand understanding of the particular environmental qualities that enable successful ageing in place in our cities and to guide efforts aimed at meeting this objective. The results suggest that encouraging the presence of more inner city retail outlets, particularly services that are utilised frequently in people’s daily lives such as supermarkets, medical services and pharmacies, would potentially help ensure residents fully engage in their local community. The connectivity of streets, footpaths and their role in facilitating the reaching of destinations are well understood as an important dimension of liveability. To encourage uptake of sustainable transport, the built environment must provide easy, accessible connections between buildings, walkways, cycle paths and public transport nodes. Wider streets, given that they take more time to cross than narrow streets, tend to .compromise safety - especially for older people. Similarly, the width of footpaths, the level of buffering, the presence of trees, lighting, seating and design of and distance between pedestrian crossings significantly affects the pedestrian experience for older people and impacts upon their choice of transportation. High density neighbourhoods also require greater levels of street fixtures and furniture for everyday life to make places more useable and comfortable for regular use. The importance of making the public realm useful and habitable for older people cannot be over-emphasised. Originality/value While older people are attracted to high density settings, there has been little empirical evidence linking liveability satisfaction with older people’s use of urban neighbourhoods. The current study examined the relationships between community/neighbourhood liveability, place and ageing to better understand the implications for those adults who age in place. The five papers presented in this thesis add to the understanding of what high density liveable age-friendly communities/ neighbourhoods are and what makes them so for older Australians. Neighbourhood liveability for older people is about being able to age in place and remain active. Issues of ageing in Australia and other areas of the developed world will become more critical in the coming decades. Creating livable communities for all ages calls for partnerships across all levels of government agencies and among different sectors within communities. The increasing percentage of older people in the community will have increasing political influence and it will be a foolish government who ignores the needs of an older society.

Reducing actuator switchings for motion control of autonomous underwater vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.

Subcarrier pairing and relay assignment with improved user fairness in a multi-user cooperative OFDM system

We consider a joint relay selection and subcarrier allocation problem that minimizes the total system power for a multi-user, multi-relay and single source cooperative OFDM based two hop system. The system is constrained to all users having a specific subcarrier requirement (user fairness). However no specific fairness constraints for relays are considered. To ensure the optimum power allocation, the subcarriers in two hops are paired with each other. We obtain an optimal subcarrier allocation for the single user case using a similar method to what is described in [1] and modify the algorithm for multiuser scenario. Although the optimality is not achieved in multiuser case the probability of all users being served fairly is improved significantly with a relatively low cost trade off.

Comparison of robust criteria for D-optimal design

This study compared the performance of a local and three robust optimality criteria in terms of the standard error for a one-parameter and a two-parameter nonlinear model with uncertainty in the parameter values. The designs were also compared in conditions where there was misspecification in the prior parameter distribution. The impact of different correlation between parameters on the optimal design was examined in the two-parameter model. The designs and standard errors were solved analytically whenever possible and numerically otherwise.

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.