Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 642 for “"Multi objective"”.
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Multi-objective cultural algorithms
… evolutionary optimization has focused on single-objective problems. On the contrary, most real-world problems involve more than one objective where these objectives may conflict with each other. </p> <p>The newest implementation of the Cultural Algorithms to solve multi-objective optimization is …
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Multi-objective optimisation with financial applications
Portfolio Optimisation is a multi-objective problem which involves finding the allocation of shares in a portfolio that optimises the likely return for a level of risk which an investor is prepared to tolerate. There have been several multi-objective evolutionary algorithms that have been used to …
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Multi-objective optimisation under deep uncertainty
… have been to deal with deep uncertainty in Multi-Criteria Decision-Making (MCDM) problems, especially with long-term decision-making processes such as strategic planning problems. To achieve these aims, we first introduced a two-stage scenario-based structure for dealing with deep …
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Computational methods for multi-objective control
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
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Multi-Objective Optimization for Public Policy
… of three factors: (i) policymakers must balance multiple objectives that often exist in tension, e.g., tradeoffs in efficiency and fairness; (ii) there are many stakeholders, with often disparate value judgments on how to best balance said objectives; and (iii) those stakeholders may not be …
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Multi-Objective optimization of arch bridges
… optimized in each case. Furthermore, a multi-objective optimization process was run on the bridge to examine the tradeoffs between the deflection and the self-weight. The weight-oriented optimization allows saving more than 60% of the weight compared to the original structure. Analyzing …
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Multi-objective Optimization in Traffic Signal Control
… the simulation is very time-consuming. Multi-objective Evolutionary Algorithms (MOEAs) are in many ways superior to traditional search methods. They have been widely utilized in traffic signal optimization problems. However, running MOEAs on traffic optimization problems using …
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Novel optimizers for multi-objective deep learning
… balancing (trade-off) between conflicting objectives, so they must be treated as Multi-objective Optimization problems. Multi-objective optimizers are suitable for training machine learning algorithms as they can minimize several loss functions simultaneously. Additionally, providing a set …
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Multi-objective evolutionary algorithms for data clustering
In this work we investigate the use of Multi-Objective metaheuristics for the data-mining task of clustering. We �first investigate methods of evaluating the quality of clustering solutions, we then propose a new Multi-Objective clustering algorithm driven by multiple measures of cluster quality …
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Algorithms for Multi-objective Network Equilibrium Problems
Multiple real life processes can be modelled as network equilibrium problems. Such models originate in areas as diverse as transportation, telecommunication, supply chains and energy. In this thesis we focus on a particular application of network equilibrium models called traffic assignment (TA). …
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Active Inference in Multi-Objective Dynamic Environments
… I make use of a dynamic environment with a multi-objective reward function to investigate the Active Inference agent's ability to learn and plan while balancing exploration and exploitation, and compare this to other Bayesian Machine Learning algorithms. In doing so, I investigate some novel …
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Multi-objective evolutionary algorithms for product design
… and Machine Learning (ML) with Evolutionary MultiObjective Optimisation (EMOO) techniques to streamline compound design. This approach automates the design process by leveraging ML to accurately predict compound properties and using EMOO to select compounds that meet various criteria. The …
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Exact And Representative Algorithms For Multi Objective Optimization
… the decision alternatives are evaluated with multiple conflicting criteria. The entire set of non-dominated solutions for practical problems is impossible to obtain with reasonable computational effort. Decision maker generally needs only a representative set of solutions from the actual …
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Multi-objective particle swarm optimisation: methods and applications.
… problems do not simply have one optimisation objective. This led to the development of multi-objective optimizers that try to look at the optimisation problem from di erent points of view and reach a set of compromised solutions among the di erent objectives. The presented research brings …
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Multi-objective optimisation of safety-critical hierarchical systems
… analysis of complex engineering models with multiple failure modes. The thesis demonstrates that, used as the fitness evaluating component of a multi-objective Genetic Algorithm, HiP-HOPS can be used to solve the problem of redundancy allocation effectively and with relative efficiency. …
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Multi-Objective evolutionary algorithms for vehicle routing problems
The Vehicle Routing Problem, which main objective is to find the lowest-cost set of routes to deliver goods to customers, has many applications in transportation services. In the past, costs have been mainly associated to the number of routes and the travel distance, however, in real-world problems …
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Heterogeneous Multi-objective Optimisation in Nuclear Power Design
… investigated in two forms: delaying a subset of objectives, and delaying a higher fidelity search. The large computational expense and extensive runtimes of nuclear power design optimisation demonstrate considerable scope for heterogeneous optimisation and the tools to accommodate it. By taking a …
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