Shih-Cheng Horng

Shih-Cheng Horng
Chaoyang University of Technology · The College of Informatics

Ph.D.

About

91
Publications
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649
Citations

Publications

Publications (91)
Article
The job shop scheduling problem is generally divided into two types according to production environments, the job shop scheduling problem with deterministic processing times and the job shop scheduling problem with uncertain processing times. Regarding the job shop scheduling problem with deterministic processing times, the shop parameters such as...
Article
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The optimization of several practical large-scale engineering systems is computationally expensive. The computationally expensive simulation optimization problems (CESOP) are concerned about the limited budget being effectively allocated to meet a stochastic objective function which required running computationally expensive simulation. Although co...
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Failures of cast-resin transformers not only reduce the reliability of power systems, but also have great effects on power quality. Partial discharges (PD) occurring in epoxy resin insulators of high-voltage electrical equipment will result in harmful effects on insulation and can cause power system blackouts. Pattern recognition of PD is a useful...
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Full-text available
The stochastic inequality constrained optimization problems (SICOPs) consider the problems of optimizing an objective function involving stochastic inequality constraints. The SICOPs belong to a category of NP-hard problems in terms of computational complexity. The ordinal optimization (OO) method offers an efficient framework for solving NP-hard p...
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Reactive volt-ampere sources planning is an effort to determine the most effective investment plan for new reactive sources at given load buses while ensuring appropriate voltage profile and satisfying operational constraints. Optimization of reactive volt-ampere sources planning is not only a difficult problem in power systems, but also a large-di...
Article
The discrete probabilistic bicriteria optimization problem (DPBOP) is a discrete optimization problem with probabilistic criteria which should be optimized simultaneously. The DPBOP belongs to a class of NP-hard problems because the computing time increases much faster when the size of the solution space increases. To solve the DPBOP efficiently, a...
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Probabilistic constrained simulation optimization problems (PCSOP) are concerned with allocating limited resources to achieve a stochastic objective function subject to a probabilistic inequality constraint. The PCSOP are NP-hard problems whose goal is to find optimal solutions using simulation in a large search space. An efficient “Ordinal Optimiz...
Article
Flow line systems are production systems in which successive operations are performed on a product in a manner so that it moves through the factory in a certain direction. This work firstly formulates a flow line system as an integer-ordered inequality-constrained simulation–optimization problem and present a stochastic simulation procedure to esti...
Article
Equality-constrained simulation optimization problems (ECSOP) involve the finding of optimal solutions by simulation within a well-defined search space under deterministic equality constraints. ECSOPs belong to the class of NP-hard problems. The large search space makes them difficult to solve in a short period using conventional optimization techn...
Conference Paper
Choosing suitable buffer setups for network-flow production lines of automated manufacturing systems to augment throughputs is a pragmatic issue. In this work, an approach merging artificial immune system (AIS) and ordinal optimization (OO) is developed to determine an optimal buffer resource allocation of a network-flow production line for maximiz...
Article
Assemble-to-order (ATO) systems refer to a manufacturing process in which a customer must first place an order before the ordered item is manufactured. An ATO system that operates under a continuous-review base-stock policy can be formulated as a stochastic simulation optimization problem (SSOP) with a huge search space, which is known as NP-hard....
Conference Paper
In this research, we present a method to solve for an optimal solution vector containing buffer allocation and service rates of the flow line production (FLP) system such that the throughput is maximized. The solution method integrates the elitist teaching-learning-based optimization (ETLBO) and optimal computing budget allocation (OCBA). At first,...
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Full-text available
In a cellular mobile system (CMS), the service area is divided into cells, each of which has numerous channels, which are shared by two types of call - new calls and handoff calls. Giving a higher priority to handoff calls than new calls is common practice. However, giving too much priority to handoff calls will result to excessive blocking of new...
Article
Please find the full text at: http://www.jultrasoundmed.org/content/34/8/1.6.short
Article
The stochastic job shop scheduling problem (SJSSP) is a kind of stochastic programming problem which transformed from job shop scheduling problem. The SJSSP is an NP-hard problem. Current solutions for the SJSSP can be classified as analytic and heuristic. However, these two methods ignored characteristics of SJSSP, which lead to large computation...
Conference Paper
The stochastic job shop scheduling problem (SJSSP) is a kind of stochastic programming problem which transformed from job shop scheduling problem. The SJSSP is an NP-hard problem. Current methods to solve the SJSSP ignored characteristics of SJSSP, which lead to large computation times and inefficient solutions. In order to efficiently solve the SJ...
Conference Paper
In this work, a dynamic channel selection and reassignment (DCSR) scheme based on distributed dynamic channel assignment (DCA) is proposed in the cellular mobile system. The proposed scheme can handle three types of constraint: co-channel (CCC), adjacent channel constraint (ACC), and co-site constraint (CSC) simultaneously. The goal is to minimize...
Article
The lithography performed on a stepper is a key process of integrated circuit manufacturing. To have a better resolution and alignment accuracy in lithography, it is important to model the overlay errors and compensate them into tolerances. The systematic overlay errors are commonly modeled as the sum of inter-field and intra-field errors. The inte...
Conference Paper
In this paper, a k-limited polling system enabling an adequate description of broadband wireless networks with centralized control is presented. A memetic algorithm (MA) is proposed to solve the k-limited polling system to obtain a good enough solution (k-limited threshold) using limited computation time. The proposed MA combines the global search...
Article
The stochastic economic lot scheduling problem (SELSP) considers the make-to-stock production of multiple standardized products on a single machine with limited capacity and set-up costs under random demands, random set-up times, and random production times. The SELSP is an NP-hard inventory problem. Current solutions for the SELSP can be classifie...
Article
A three-phase memetic algorithm (MA) is proposed to find a suboptimal solution for real-time combinatorial stochastic simulation optimization (CSSO) problems with large discrete solution space. In phase 1, a genetic algorithm assisted by an offline global surrogate model is applied to find N good diversified solutions. In phase 2, a probabilistic l...
Article
Giloblastoma multiforme (GBM) is the most aggressive brain neoplasm, and patients have a poor prognosis after radiation and chemotherapy. The chemotherapy protocols still marginally improve the anti-tumor effect of patients with glioblastoma because the therapeutic dosage of many drugs is impeded by the blood-brain barrier (BBB). The use of liposom...
Article
This work proposes an evolutionary algorithm (EA) that is assisted by a surrogate model in the framework of ordinal optimization (OO) and optimal computing budget allocation (OCBA) for use in solving the real-time combinatorial stochastic simulation optimization problem with a huge discrete solution space. For real-time applications, an off-line tr...
Article
In this paper, we combine evolution strategy (ES) with ordinal optimization (OO), abbreviated as ES + OO, to solve real-time combinatorial stochastic simulation optimization problems with huge discrete solution space. The first step of ES + OO is to use an artificial neural network (ANN) to construct a surrogate model to roughly evaluate the object...
Article
The permeability of the blood-brain barrier (BBB) can be enhanced by focused ultrasound (FUS) in localized regions with applications of ultrasound contrast agent (UCA). The purpose of this study was to evaluate the dose distribution of Evans blue (EB) in the targeted brain by sonication with treatment strategy. FUS exposure was applied with an ultr...
Article
Within the framework of a successive quadratic programming method for problems involving discrete variables on power systems, this work formulates the distributed optimal power flow with continuous and discrete variables problems (Distributed OPFCDP) and distributed state estimation with continuous and discrete variables problems (Distributed SECDP...
Conference Paper
The stochastic economic lot scheduling problem (SELSP) considers the make-to-stock production of multiple standardized products on a single machine with limited capacity, possibly random set-up times under random demands, and possibly random processing times. The SELSP is an NP-hard inventory problem. The solution methods for solving the SELSP may...
Article
This work proposes a two-phase iterative simulation optimization approach to solve the optimal voltampere reactive (VAR) sources planning problem. In the upper phase, an Ordinal Optimization (OO)-based method is employed as the optimization methodology, which performs ranking and selection to choose better solutions from a candidate solution set ba...
Article
In this paper, a multi-stage ordinal optimization (OO) based approach is proposed to solve for a good enough schedule of stochastic classical job shop scheduling problems using limited computing time. The proposed approach consists of exploration and exploitation stage. The exploration stage uses a genetic algorithm (GA) to select a good candidate...
Article
Full-text available
In this work, an ordinal optimization-based evolution algorithm (OOEA) is proposed to solve a problem for a good enough target inventory level of the assemble-to-order (ATO) system. First, the ATO system is formulated as a combinatorial optimization problem with integer variables that possesses a huge solution space. Next, the genetic algorithm is...
Article
This work proposes a method for embedding evolutionary strategy (ES) in ordinal optimization (OO), abbreviated as ESOO, for solving real-time hard optimization problems with time-consuming evaluation of the objective function and a huge discrete solution space. Firstly, an approximate model that is based on a radial basis function (RBF) network is...
Article
Full-text available
In this paper, the problem of minimizing overkills and re-probes in wafer probe testing is formulated as a multiobjective optimization problem. Overkill is a measure of good dies that were considered bad and re-probe is an additional manual probe testing to save overkills. The goal is to provide an optimal setting of threshold values for engineers...
Conference Paper
In this work, a meta-heuristic approach integrated the genetic algorithm (GA) with ranking and selection (R&S) is proposed to solve for a good enough solution of the hard stochastic simulation optimization problem (SSOP) with huge solution space. First, a rough model is used as a fitness evaluation in the GA to select N roughly good solutions from...
Conference Paper
In this paper, a two-stage algorithm based on ordinal optimization (OO) theory is proposed to solve the booking limits problem with huge discrete solution space. First, a crude model with a small amount of simulation replications is used as a fitness evaluation in particle swarm optimization (PSO) algorithm to select N candidate solutions from solu...
Article
The central nervous system vasculature consists of a tightly sealed endothelium that forms the blood-brain barrier (BBB); these blood vessels are impermeable to large-molecular-size agents. The aim of this study was to determine the influence of prenatal ultrasound exposure on blood-brain barrier (BBB) integrity as measured by the permeation of Eva...
Article
In this paper, the decentralized optimal power flow with continuous and discrete control variables problem is firstly formulated as a NP-hard optimization problem - Block Additive constrained with Continuous and Discrete variables (BACD) problem. Secondly, an algorithm of embedding sensitivity theory (ST) in ordinal optimization (OO), abbreviated a...
Article
The purpose of this study is to investigate the dose-dependent effects of ultrasound contrast agent (UCA) on the changes of peak systolic velocity (PSV) and pulsatility index (PI) in the arteries of 24 male Sprague-Dawley rats. The rats were sonicated with 1.0-MHz pulsed high-intensity focused ultrasound (HIFU) at two acoustic powers, 15 W and 30 W...
Article
Full-text available
The purpose of this study was to evaluate the permeability of the blood-brain barrier (BBB) after focused ultrasound (FUS) exposure and to investigate if such an approach increases the tumor-to-ipsilateral brain permeability ratio. Normal rats and F98 glioma-bearing rats were injected intravenously with Evans blue (EB); these treatments took place...
Article
In this paper, we have formulated the resource allocation optimization problem for expanding service and increasing reliability of a grid computing system. The formulated problem is a combinational optimization as well as an NP-hard problem. We firstly decompose this problem into a minimizing budget problem and a maximizing reliability problem. An...
Article
We propose a distributed dynamic channel assignment (DDCA) method to handle the co-channel constraint (CCC), adjacent channel constraint (ACC) and co-site constraint (CSC) simultaneously. In the proposed DDCA method, we introduce the channel state concept and develop the channel state table based channel selection and channel reassignment schemes....
Article
Full-text available
The use of pulsed high-intensity focused ultrasound (HIFU) with an ultrasound contrast agent (UCA) has been shown to disrupt the blood-brain barrier (BBB) noninvasively and reversibly in the targeted regions. This study evaluated the relative permeability of the blood-tumor barrier (BTB) after sonication by pulsed HIFU. Entry into the brain of chem...
Article
An Experiment for Estimating Accurate States in Distributed Power Systems
Article
In our previous work, a parallel dual-type (PDt) method was presented for solving a class of weighted-least-squares (WLS) with equality constraints problems and obtained some successful results. In this work, we propose a more general parallel dual-type (MPDt) method using the framework of the PDt method to solve more extensive WLS problems (with e...
Article
Full-text available
The purpose of this study is to determine the association between fetal nasal bone length (NBL) and gestational age (GA), biparietal diameter (BPD) and head circumference (HC) in women undergoing prenatal assessments and Down syndrome screening. Cross-sectional data were obtained from 3,003 women with singleton pregnancies who underwent a prenatal...
Article
This work presents a two-stage ordinal optimization theory-based approach for solving the throughput maximization problems with power constraints of sub-carrier assignment and power allocation in multi-user orthogonal frequency division multiplexing uplink systems. In the first stage, a crude but efficient model is employed to evaluate the performa...
Article
A non-polynomial (NP)-hard combinatorial optimization problem that is associated with expanding service capacities and increasing service reliability in grid-based utility computing is investigated in this paper. The considered problem is decomposed into master and slave subproblems, with theoretical justification, and a computationally efficient t...
Article
In this paper, we propose a hierarchical fuzzy clustering decision tree (HFCDT) for the classification problem with large number of classes and continuous attributes. The HFCDT combines a division-degree matrix based hierarchal clustering technique with the entropy-based C4.5 decision tree algorithm. A hierarchical clustering concept is introduced...
Article
In this paper, a cyclic service system enabling an adequate description of the control mechanism of the centralized broadband wireless networks with k-limited discipline is presented. An arrival rate prediction method combined with the ordinal optimization (OO) theory-based algorithm is proposed to find a good enough k-limited discipline for the cy...
Article
In this paper, we propose an ordinal optimization (OO) based algorithm for solving the resource allocation optimization problem of grid computing system to maximize the service reliability. An approximate model is firstly proposed to estimate the service reliability of a resource allocation design within a tolerable computation time. Next, we emplo...
Article
In this paper, we combine the particle swarm (PS) with ordinal optimization (OO), abbreviated as CPSOO, to solve for a good enough solution of the stochastic simulation optimization problem (SSOP) with huge search space. First, a rough model using stochastic simulation with a small amount of test samples will be used as a fitness function evaluatio...
Article
To investigate the correlation between the contrast-enhanced magnetic resonance imaging (MRI) signal and the duration of blood-brain barrier (BBB) disruption induced by focused ultrasound (FUS). FUS was applied to 45 rat brains in the presence of microbubbles, and these rats were scanned on a 3T MRI system at several timepoints. The rat brains were...
Conference Paper
In this paper, an ordinal optimization (OO) based algorithm is applied to minimize the overkills under a tolerable level of re-probes in a wafer probe testing process, which is formulated as a constrained stochastic simulation optimization problem that consists of a huge input-variable space formed by the vector of threshold values in the testing p...
Article
Full-text available
It has been shown that B-mode ultrasound can be useful for the real-time visualization of high-intensity focused ultrasound (HIFU) treatment. The aim of this study is to demonstrate the real-time ultrasound observation of functional changes when a vessel is exposed to pulsed-HIFU in the presence of preformed microbubbles. Using in vivo experiments,...
Conference Paper
In this paper, an ordinal optimization theory based approach is proposed to solve for a good enough solution of the G/G/1/K cyclic service system with k-limited discipline using reasonable computation time. First, a rough model using stochastic simulation with a small amount of served customers will be used as a fitness function evaluation in parti...
Article
The overlay modeling errors are commonly modeled as the sum of inter-field and intra-field errors in lithography process of wafer stepper. The inter-field errors characterize the global effect while the intra-field errors represent the local effect. To have a better resolution and alignment accuracy, it is important to model the overlay errors and...
Article
In this paper, we propose an ordinal optimization (OO) theory-based algorithm to solve the yet to be explored distributed state estimation with continuous and discrete variables problems (DSECDP) of large distributed power systems. The proposed algorithm copes with a huge amount of computational complexity problem in large distributed systems and o...
Article
In this paper, we propose a parallelized Dual Projected Pseudo Quasi-Newton (parallelized DPPQN) based Expert System method to solve a kind of distributed constrained optimization problem. The proposed parallelized DPPQN based Expert System method differs from the conventional Lagrange method by treating the inequality constraints as the domain of...
Article
This work formulates optimal power flow with continuous and discrete variables problems (OPFCDP) and state estimation with continuous and discrete variables problems (SECDP) as classes of quadratic programming with continuous and discrete variables problems (QCDP). This work also applies an ordinal optimization (OO) theory-based two-stage algorithm...
Article
In this paper, we propose a fuzzy clustering decision tree (FCDT) for the classification problem with large number of classes and continuous attributes. A hierarchical clustering concept is introduced to achieve a finer fuzzy partition. The proposed clustering algorithm split the data set into leaf clusters using splitting attributes based on a sep...
Article
In this paper, we proposed an arrival rate prediction method to combine with the previously developed ordinal optimization (OO) theory based algorithm for the G/G/1/K polling system with the k-limited service discipline so as to achieve the real-time application purpose. We employ the Box-Jenkins method for predicting the arrival rate every ¿t peri...
Article
In this paper, we focus on the difficulties of resource recycling problems relating to the used Iron and/or Aluminum cans. Based on the feedback control theory and combining with micro-chip processor, sensors, phonic chip, oil-compressor and mechanism technology, we design an interactive resource recycling Expert System –“Recycling Squeezed Cans De...
Article
In this paper, an ordinal optimization based approach is proposed to solve for a good enough schedule that minimizes expected sum of storage expenses and tardiness penalties of stochastic classical job shop scheduling problem using limited computation time. The proposed approach consists of exploration and exploitation stage. The exploration stage...
Article
In this paper, we have proposed an ordinal optimization theory-based two-stage algorithm to solve for a good enough solution of the stochastic simulation optimization problem with huge input-variable space Θ. In the first stage, we construct a crude but effective model for the considered problem based on an artificial neural network. This crude mod...
Article
In this paper, we focus on the frequent glitches of general family cars. Based on the Neural Network theory and combining with the Micro-chip processor technology, we design an expert system-“Integrated Cars Repairing Tools” (ICRT) and the size of the proposed ICRT is quite small and achieves the following attractive functions: (1) Portable Electri...
Article
In this paper, we present a parallel dual-type (PDT) algorithm for solving a strictly convex quadratic programming problem with equality and box constraints. The PDT algorithm is suitable for distributed implementation and can be used as a basic optimization module for handling optimization problems of large distributed systems. Besides, combining...
Article
In this paper, we propose an ordinal optimization theory based algorithm to solve the optimization problem of G/G/1/K polling system with k-limited service discipline for a good enough solution using limited computation time. We assume that the arrival rates do not deteriorate visibly within a very short period. Our approach consists of two stages....
Article
In this paper, the authors present a noble heuristic reading machine for blind people. The goal of this paper is to use intelligent-control method to settle down the reading machine by a touch-pat device for blind people. The proposed" A noble heuristic reading device for blind people"can efficiently help blind people for reading and train the blin...
Article
In this paper, we proposed a design for a class of temperature stabilization system based on the feedback control theory and the corresponding technology of microchip MC89C51 and sensors theory. Besides, the proposed design was implemented on a set of temperature control system to determine whether the current status of fishes tank fitting fishes s...
Article
Full-text available
An algorithm, based on ordinal optimisation (OO) and sensitive theories, is presented to solve a class of constrained weight least square problems with continuous and discrete variables. the proposed algorithm can cope with an enormous amount of computational complexity problems and has a high probability of obtaining a good enough solution accordi...
Article
We propose a classification-based fault detection and isolation scheme for the ion implanter. The proposed scheme consists of two parts: 1) the classification part and 2) the fault detection and isolation part. In the classification part, we propose a hybrid classification tree (HCT) with learning capability to classify the recipe of a working wafe...
Article
In this correspondence, we have formulated a stochastic optimization problem to find the optimal threshold values to reduce the overkills of dies under a tolerable retest level in wafer testing process. The problem is a hard optimization problem with a huge solution space. We propose an ordinal optimization theory-based two-level algorithm to solve...
Article
Full-text available
In this paper, we propose an ordinal optimization approach to solve for a good enough solution of the stochastic simulation optimization problem with huge decision-variable space. We apply the proposed ordinal optimization algorithm to G/G/1/K polling systems to solve for a good enough number-limited service discipline to minimize the weighting ave...
Conference Paper
In this paper, we propose a hybrid classification tree (HCT) to classify the products of complicated machines in flexible manufacturing systems. The HCT combines a proposed clustering algorithm with the classification and regression tree (CART) to take the advantage of the constant property of control settings during any process step for a type of...
Conference Paper
Full-text available
In this paper, we propose a fault detection scheme for an ion implanter using the classification approach. We employ a previously developed hierarchical fuzzy rule based classifier (HFRBC) to classify the recipe of a working wafer in the ion implanter. The classification errors for various recipes of the HFRBC are treated as the accuracy of the cla...
Conference Paper
In this paper, we propose a hierarchical fuzzy rule based classifier (HFRBC) for the classification problem with large number of classes and continuous attributes. A hierarchical clustering concept is introduced to achieve a finer fuzzy partition. Critical attributes are used to perform the cluster splitting and generate a cluster splitting tree. T...
Conference Paper
Reducing overkills is one of the main objectives in the wafer testing process, however the major mean to prevent overkills is retest. In this paper, we formulate the problem of reducing overkills and retests as a stochastic optimization problem to determine optimal threshold values concerning the number of good dies and the number of bins in a lot...
Conference Paper
We propose a new dual projected pseudo quasi-Newton method for discrete-time linear quadratic optimal control problems of a large-scale multi-destination network. Our method has successfully overcome the difficulties caused by large dimensions and inequality constraints by having a constant Hessian matrix and an efficient successive projection meth...

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