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.

Results

Showing 1 to 8 of 8 for “"Optimal Computing"”.

  1. OPTIMAL COMPUTING BUDGET ALLOCATION FOR SIMULATION BASED OPTIMIZATION AND COMPLEX DECISION MAKING

    Optimal Computing Budget Allocation (OCBA) considers the problem how to get a best result based on the simulation output under a computing budget constraint. It is not only an efficient ranking and selection procedure for simulation problems with finite candidate solutions but also an attractive …

    nus Repository record for OPTIMAL COMPUTING BUDGET ALLOCATION FOR SIMULATION BASED OPTIMIZATION AND COMPLEX DECISION MAKING (opens in a new tab)

  2. ON SOLVING MULTI-OBJECTIVE SIMULATION OPTIMIZATION BY OPTIMAL COMPUTING BUDGET ALLOCATION AND RANDOM SEARCH

    … objectives, analytical models and closed-form optimal solutions are usually hard to formulate and derive. These issues can be addressed by multi-objective simulation optimization, which employs efficient simulation to evaluate solutions' performance and such information is further used to guide …

    nus Repository record for ON SOLVING MULTI-OBJECTIVE SIMULATION OPTIMIZATION BY OPTIMAL COMPUTING BUDGET ALLOCATION AND RANDOM SEARCH (opens in a new tab)

  3. Using metaheuristics with the ranking and selection indifference-zone procedure MMY in problems with many objectives

    … exploring these spaces and approximating Pareto-optimal solutions, they lack statistical guarantees, making the reliability of their outputs uncertain. In contrast, ranking and selection (R&S) procedures provide statistical guarantees, specifically for the probability of correct selection …

    stellenbosch Repository record for Using metaheuristics with the ranking and selection indifference-zone procedure MMY in problems with many objectives (opens in a new tab)

  4. New model-based methods for non-differentiable optimization

    … and applies a gradient-based method to find the optimal parameter such that the corresponding distribution has the best capability to generate optimal solution(s) to the original discrete problem. The second algorithm, annealing-GASS, uses Boltzmann distribution as the parameterized probabilistic …

    uiuc Repository record for New model-based methods for non-differentiable optimization (opens in a new tab)

  5. Efficient selection of a set of good enough designs with complexity preference

    This thesis briefly reviews the important methods involved in solving the best design selection problem in the discrete-event system simulation. The selection of one or several best designs is a common problem people meet in real situations. The research originally focused on the one best design …

    uiuc Repository record for Efficient selection of a set of good enough designs with complexity preference (opens in a new tab)

  6. Problems on decision making under uncertainty

    … cases; the proposed methods maintain near-optimal solution quality. Even though the applicability of the techniques developed in our work cannot be limited to a few examples, the applications addressed in our work include post-hazard large-scale real-world community recovery management, …

    colostate Repository record for Problems on decision making under uncertainty (opens in a new tab)