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Articles 1 - 4 of 4
Full-Text Articles in Engineering
Adaptive Sampling Trust-Region Methods For Derivative-Based And Derivative-Free Simulation Optimization Problems, Sara Shashaani
Adaptive Sampling Trust-Region Methods For Derivative-Based And Derivative-Free Simulation Optimization Problems, Sara Shashaani
Open Access Dissertations
We consider unconstrained optimization problems where only “stochastic” estimates of the objective function are observable as replicates from a Monte Carlo simulation oracle. In the first study we assume that the function gradients are directly observable through the Monte Carlo simulation. We propose ASTRO, which is an adaptive sampling based trust-region optimization method where a stochastic local model is constructed, optimized, and updated iteratively. ASTRO is a derivative-based algorithm and provides almost sure convergence to a first-order critical point with good practical performance. In the second study the Monte Carlo simulation is assumed to provide no direct observations of the …
Parametric Approaches To Fractional Programs: Analytical And Empirical Study, Chong Hyun Park
Parametric Approaches To Fractional Programs: Analytical And Empirical Study, Chong Hyun Park
Open Access Dissertations
Fractional programming is used to model problems where the objective function is a ratio of functions. A parametric modeling approach provides effective technique for obtaining optimal solutions of these fractional programming problems. Although many heuristic algorithms have been proposed and assessed relative to each other, there are limited theoretical studies on the number of steps to obtain the solution. In this dissertation, I focus on the linear fractional combinatorial optimization problem, a special case of fractional programming where all functions in the objective function and constraints are linear and all variables are binary that model certain combinatorial structures. Two parametric …
Best Matching Processes In Distributed Systems, Mohsen Moghaddam
Best Matching Processes In Distributed Systems, Mohsen Moghaddam
Open Access Dissertations
The growing complexity and dynamic behavior of modern manufacturing and service industries along with competitive and globalized markets have gradually transformed traditional centralized systems into distributed networks of e- (electronic) Systems. Emerging examples include e-Factories, virtual enterprises, smart farms, automated warehouses, and intelligent transportation systems. These (and similar) distributed systems, regardless of context and application, have a property in common: They all involve certain types of interactions (collaborative, competitive, or both) among their distributed individuals—from clusters of passive sensors and machines to complex networks of computers, intelligent robots, humans, and enterprises. Having this common property, such systems may encounter common …
Algorithmic And Mathematical Programming Approaches To Scheduling Problems With Energy-Based Objectives, Kan Fang
Open Access Dissertations
This dissertation studies scheduling as a means to address the increasing concerns related to energy consumption and electricity cost in manufacturing enterprises. Two classes of problems are considered in this dissertation: (i) minimizing the makespan in a permutation flow shop with peak power consumption constraints (the PFSPP problem for short) and (ii) minimizing the total electricity cost on a single machine under time-of-use tariffs (the SMSEC problem for short). We incorporate the technology of dynamic speed scaling and the variable pricing of electricity into these scheduling problems to improve energy efficiency in manufacturing.The challenge in the PFSPP problem is to …