Simulation Optimization for MRO Systems Operations

2017 ◽  
Vol 34 (02) ◽  
pp. 1750003 ◽  
Author(s):  
Pai Liu ◽  
Xi Zhang ◽  
Zhongshun Shi ◽  
Zewen Huang
Keyword(s):  
Optimization Problem ◽  
Simulation Optimization ◽  
Difficult Problem ◽  
Asymptotic Convergence ◽  
High Quality ◽  
Nested Partitions ◽  
Material Recovery ◽  
Processing Times ◽  
Key Characteristics ◽  
Two Hybrid

In this paper, we address the scheduling issues in a class of maintenance, repair and overhaul systems. By considering all key characteristics such as disassembly, material recovery uncertainty, material matching requirements, stochastic routings and variable processing times, the scheduling problem is formulated into a simulation optimization problem. To solve this difficult problem, we developed two hybrid algorithms based on nested partitions method and optimal computing budged allocation technology. Asymptotic convergence of these two algorithms is proved and numerical results show that the proposed algorithms can generate high quality solutions which outperform the performance of many heuristics.

Effect of processing time on the quality of dry-cured ham obtained from a native pig breed (Chato Murciano)

2015 ◽  
Vol 55 (1) ◽  
pp. 113 ◽  
Author(s):  
Eva Salazar ◽  
Adela Abellán ◽  
José M. Cayuela ◽  
Ángel Poto ◽  
Francisco Girón ◽  
...  
Keyword(s):  
Processing Time ◽  
Consumer Preference ◽  
Ripening Stage ◽  
High Quality ◽  
Processing Times ◽  
Consumer Study ◽  
Dry Cured Ham ◽  
Sensory Changes ◽  
Sensory Parameters

The compositional and sensory parameters of Chato Murciano dry-cured ham at different ripening times (14, 18, 22 and 24 months of processing) were studied. A sensory consumer study of dry-cured ham with a short ripening stage (14 months of processing) and a similar ham with a long ripening stage (22 months of processing) was carried out. Dry-cured hams remained in the ripening stage at 18−20°C and 70–75% relative humidity. The different processing times studied had no effect on the ash, intramuscular fat, sodium chloride and protein contents of the final ham, but significantly affected the moisture (P < 0.05) and saturated (P < 0.01) and monounsaturated (P < 0.05) fatty acid contents. Sensory analysis showed that processing time enhanced redness, fat colour, all of the odour and flavour traits studied, and all the texture traits except juiciness. In the taste profile, only saltiness showed a significant increase. However, sensory changes were only significant up to 22 months of processing (for most of the parameters), the resulting ham showing higher level of consumer preference and acceptability than dry-cured ham with the shorter ripening. Based on these results, it is recommended that an appropriate processing time to obtain a high-quality Chato Murciano dry-cured ham is 22 months.

A Study on Efficient Computing Budget Allocation for a Two-Stage Problem

2021 ◽  
pp. 2050044
Author(s):  
Tianxiang Wang ◽  
Jie Xu ◽  
Jian-Qiang Hu
Keyword(s):  
Optimization Problem ◽  
Simulation Optimization ◽  
Risk Measure ◽  
Budget Allocation ◽  
Optimal Decision ◽  
Two Stage ◽  
Second Stage ◽  
Allocation Procedure ◽  
Optimal Computing Budget Allocation ◽  
Sequential Allocation

We consider how to allocate simulation budget to estimate the risk measure of a system in a two-stage simulation optimization problem. In this problem, the first stage simulation generates scenarios that serve as inputs to the second stage simulation. For each sampled first stage scenario, the second stage procedure solves a simulation optimization problem by evaluating a number of decisions and selecting the optimal decision for the scenario. It also provides the estimated performance of the system over all sampled first stage scenarios to estimate the system’s reliability or risk measure, which is defined as the probability of the system’s performance exceeding a given threshold under various scenarios. Usually, such a two-stage procedure is very computationally expensive. To address this challenge, we propose a simulation budget allocation procedure to improve the computational efficiency for two-stage simulation optimization. After generating first stage scenarios, a sequential allocation procedure selects the scenario to simulate, followed by an optimal computing budget allocation scheme that determines the decision to simulate in the second stage simulation. Numerical experiments show that the proposed procedure significantly improves the efficiency of the two-stage simulation optimization for estimating system’s reliability.

The GUI-Based Simulation Optimization Platform for Fault Grey Prediction of Diesel Engine

2014 ◽  
Vol 687-691 ◽  
pp. 1049-1053
Author(s):  
Xiang Huan Zu ◽  
Jing Wang ◽  
Chuan Lei Yang ◽  
Xuan Qin
Keyword(s):  
Diesel Engine ◽  
Optimization Problem ◽  
Simulation Optimization ◽  
Simulation Platform ◽  
Grey Prediction ◽  
Post Processing ◽  
Input Output ◽  
Operating Environment ◽  
Modeling Process ◽  
Simulation Calculation

The simulation optimization platform for fault grey prediction of diesel engine is designed by MATLAB GUI, to ensure a reliable operating environment. The GM (1,1) model and improved models are presented in the platform to solve the optimization problem of prediction precision. The platform sets input, output, simulation calculation and post processing functions as one and is compiled to the executable program at last . As is proved by simulation examples, the platform simplifies the modeling process and improves the efficiency of the simulation, It is confirmed that the simulation platform for fault grey prediction of diesel engine is practical.

Optimization of chemical vapor infiltration with simultaneous powder formation

2000 ◽  
Vol 15 (12) ◽  
pp. 2695-2705 ◽  
Author(s):  
A. Ditkowski ◽  
D. Gottlieb ◽  
B. W. Sheldon
Keyword(s):  
Homogeneous Nucleation ◽  
Optimization Problem ◽  
Chemical Vapor ◽  
Chemical Vapor Infiltration ◽  
Governing Equations ◽  
Processing Times ◽  
Dilute Gases ◽  
Asymptotic Expressions ◽  
Powder Formation ◽  
Vapor Infiltration

A key difficulty in isothermal, isobaric chemical vapor infiltration is the long processing times that are typically required. With this in mind, it was important to minimize infiltration times. This optimization problem was addressed here, using a relatively simple model for dilute gases. The results provided useful asymptotic expressions for the minimum time and corresponding conditions. These approximations were quantitatively accurate for most cases of interest, where relatively uniform infiltration was required. They also provided useful quantitative insight in cases where less uniformity was required. The effects of homogeneous nucleation were also investigated. This does not effect the governing equations for infiltration of a porous body; however, powder formation can restrict the range of permissible infiltration conditions. This was analyzed for the case of carbon infiltration from methane.

High Quality Characteristics of Briquette Fuel Based on Physical Appearances and Electrical Induction

2016 ◽  
Vol 848 ◽  
pp. 56-59
Author(s):  
Duongruitai Nicomrat ◽  
Parinya Somkid ◽  
Kitti Chuaiwan
Keyword(s):  
Production Process ◽  
Agricultural Waste ◽  
High Heat ◽  
Heat Output ◽  
Key Factors ◽  
High Quality ◽  
Key Characteristics ◽  
Electrical Induction ◽  
Further Development

At present, charcoal briquette fuel, a source of heat energy and mostly made from agricultural waste materials, are popular in the markets because of their high constant heat output. It helps reduce pollution, and produce no sparks while burning, but varied due to different types of materials, burning protocols, temperature, and pressure used. In this study, the research team have studied the characteristics of high quality fuel briquettes for possible further development of standard indicators of briquette fuel production process. In the study, key factors of the Charcoal fuel features composed of high qualities of physical characteristics and electrical induction. Activated carbon and coconut shell charcoal types were showed to be great materials. The production process involved aerobic burning at 800-900oC for at least 3 hours, grinding and mixing with starch binder. The briquettes’ electrical conductivity was especially lower than 10 kΩ. High heat production was obtained at least 6000 Cal/g while ground charcoal possessed with the sizes were varied. Under microscopy, the charcoal particle sizes were in a range of 50-100 μm for 30-50% (w/w), size of 10-50 μm for 20-40% (w/w) and distinctive numbers of holes greater than 300 μ to 1 mm were rarely observed. Therefore, with key characteristics of charcoal briquette fuel, it could be further applied for development the indicator as well as instruments to measure the quality of the briquette.

scholarly journals Improving model-based fNIRS analysis using mesh-based anatomical and light-transport models

2020 ◽  
Author(s):  
Anh Phong Tran ◽  
Shijie Yan ◽  
Qianqian Fang
Keyword(s):  
Computational Models ◽  
Near Infrared ◽  
Light Transport ◽  
Tetrahedral Mesh ◽  
High Quality ◽  
Functional Near Infrared Spectroscopy ◽  
Processing Times ◽  
Complex Anatomy ◽  
Anatomical Modeling ◽  
Mesh Models

AbstractSignificanceFunctional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy.AimWe aim to highlight the importance of accurate anatomical modeling in the context of fNIRS, and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis.ApproachWe have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multi-layered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element based photon simulations for fNIRS studies.ResultsA variety of high quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare 3 brain anatomical models - the voxel-based brain segmentation, tetrahedral brain mesh and layered-slab brain model, and demonstrate noticeable discrepancies in brain partial-pathlengths when using approximated brain anatomies, ranging between −1.5-23% with the voxelated brain and 36-166% with the layered-slab brain.ConclusionThe generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes “Brain2Mesh” and “Iso2Mesh” are freely available at http://mcx.space/brain2mesh.

scholarly journals Hierarchical minimization of two maximum costs on a bounded serial-batching machine

2020 ◽  
Author(s):  
Cheng He ◽  
Hao Lin ◽  
Li Li
Keyword(s):  
Processing Time ◽  
Optimization Problem ◽  
Setup Time ◽  
Time Algorithm ◽  
Hierarchical Optimization ◽  
Objective Functions ◽  
Processing Times ◽  
Hierarchical Minimization ◽  
Batching Machine ◽  
Special Case

This paper studies a hierarchical optimization problem of scheduling $n$ jobs on a serial-batching machine, in which two objective functions are maximum costs. By a hierarchical optimization problem, we mean the problem of optimizing the secondary criterion under the constraint that the primary criterion is optimized. A serial-batching machine is a machine that can handle up to $b$ jobs in a batch and jobs in a batch start and complete respectively at the same time and the processing time of a batch is equal to the sum of the processing times of jobs in the batch. When a new batch starts, a constant setup time $s$ occurs. We confine ourselves to the bounded model, where $b<n$. We present an $O(n^4)$-time algorithm for this hierarchical optimization problem. For the special case where two objective functions are maximum lateness, we give an $O(n^3\log n)$-time algorithm.

scholarly journals Genetiniai algoritmai komivojažieriaus uždaviniui: negatyvieji ir pozityvieji aspektai*

2009 ◽  
Vol 50 ◽  
pp. 173-180
Author(s):  
Alfonsas Misevičius ◽  
Andrius Blažinskas ◽  
Jonas Blonskis ◽  
Vytautas Bukšnaitis
Keyword(s):  
Genetic Algorithms ◽  
Traveling Salesman Problem ◽  
Optimization Problem ◽  
Combinatorial Optimization Problem ◽  
Traveling Salesman ◽  
High Quality ◽  
Genetic Search ◽  
Local Improvement ◽  
Effi Ciency ◽  
The Traveling Salesman Problem

Šiame straipsnyje nagrinėjami klausimai, susiję su genetinių algoritmų taikymu, sprendžiant gerai žinomą kombinatorinio optimizavimo uždavinį – komivojažieriaus uždavinį (KU) (angl. traveling salesman problem). Svarstoma, jog genetinio algoritmo efektyvumui didelę įtaką turi uždavinio specifi nės savybės, todėl labai svarbu kūrybiškai sudaryti genetinį algoritmą konkrečiam sprendžiamam uždaviniui. Pateikiami eksperimentų, atliktų su realizuotu genetiniu algoritmu, rezultatai, iliustruojantys skirtingų veiksnių įtaką rezultatų kokybei. Konstatuojama, kad tinkamas genetinių operatorių ir lokaliojo individų (sprendinių) gerinimo derinimas leidžia gerokai padidinti genetinės paieškos efektyvumą.On the Genetic Algorithms for the Traveling Salesman Problem: Negative and Positive AspectsAlfonsas Misevičius, Andrius Blažinskas, Jonas Blonskis, Vytautas Bukšnaitis SummaryIn this paper, we discuss some issues related to the application of genetic algorithms (GAs) to the well-known combinatorial optimization problem – the traveling salesman problem (TSP). The results obtained from the experiments with the different variants of the genetic algorithm are presented as well. Based on these results, it is concluded that the effi ciency of the genetic search is much infl uenced by both the specifi c nature of the problem and the features of the algorithm itself. In particular, it should be emphasized that the incorporation of the (postcrossover) procedures for the local improvement of offspring has one of the crucial roles in obtaining high-quality solutions.

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