scholarly journals Optimizing the Tolerance for the Products with Multi-Dimensional Chains via Simulated Annealing

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1780
Author(s):  
Chen-Kun Tsung
Keyword(s):  
Simulated Annealing ◽  
Product Quality ◽  
High Performance ◽  
Dimensional Chain ◽  
Real World Application ◽  
Hard Constraints ◽  
Feasibility Evaluation ◽  
Algorithm Configuration ◽  
Assembly Problem ◽  
Assembly Guidance

The assembly is the last process of controlling the product quality during manufacturing. The installation guidance should provide the appropriate assembly information, e.g., to specify the components in each product. The installation guidance with low quality results in rework or the resource waste from the failure products. This article extends the dimensional chain assembly problem proposed by Tsung et al. to consider the multiple dimensional chains in the product. Since there are multiple dimensional chains in a product, the installation guidance should consider inseparability and acceptability as computing the installation guidance. The inseparability means that the qualities of all dimensional chains in the part should be evaluated together without separation, while the acceptability stands for that the size of each product should be satisfied with the specification. The simulated annealing (SA) algorithm is applied to design the assembly guidance optimizer named as AGOMDC to compute the assembly guidance in the dimensional chain assembly problem with multiple dimensional chains. Since SA has high performance in searching neighbor solutions, the proposed approach could converge rapidly. Thus, proposed AGOMDC could be applied in real-world application for the implementation consideration. The simulations consist of two parts: the feasibility evaluation and the algorithm configuration discussion. The first part is to verify the inseparability and acceptability that are the hard constraints of the assembly problem for the proposed AGOMDC, and the second one is to analyze the algorithm configurations to calculate the assembly guidance with 80% quality. The simulation results show that the inseparability and acceptability are achieved, while the proposed AGOMDC only requires more than two seconds to derive the results. Moreover, the recommended algorithm configurations are derived for evaluate the required running time and product quality. The configurations with product quality 80% are that the temperature descent rate is 0.9, the initial temperature is larger than 1000, and the iteration recommended function is derived based on the problem scale. The proposed AGOMDC not only helps the company to save the time of rework and prevent the resource waste of the failure products, but is also valuable for the automatic assembly in scheduling the assembly processes.

The Product Portfolio and Man's Best Friend

1982 ◽  
Vol 25 (1) ◽  
pp. 84-95 ◽  
Author(s):  
Donald C. Hambrick ◽  
Ian C. MacMillan
Keyword(s):  
Product Quality ◽  
High Performance ◽  
Product Portfolio ◽  
Best Friend

Boston Consulting Group's Dogs reconsidered: Their efficiency, superior product quality, and focus mean high performance.

scholarly journals GLOBAL OPTIMIZATION OF GRILLAGES USING SIMULATED ANNEALING AND HIGH PERFORMANCE COMPUTING

2010 ◽  
Vol 16 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Dmitrij Šešok ◽  
Jonas Mockus ◽  
Rimantas Belevičius ◽  
Arnas Kačeniauskas
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
High Performance ◽  
Practical Problem ◽  
Real Life ◽  
Optimization Methods ◽  
Medium Size ◽  
Reactive Force ◽  
Standard Medium ◽  
Performance Computing

The aim is to investigate ways of increasing the efficiency of grillage optimization. Following this general aim, two well‐known optimization methods, namely the Genetic Algorithm (GA) and Simulated Annealing (SA), were compared using some standard medium size (10 and 15 piles) examples. The objective function was the maximal vertical reactive force at a support. Coordinates of piles were optimization variables. SA wins and was applied to real‐life problem (55 piles) by parallel computations performed using a powerful cluster. New element is comparison of SA with GA and application of SA to a practical problem of grillage optimization. Santrauka Straipsnio tikslas - ištirti galimus rostverkiniu pamatu optimizavimo būdus. Siekiant šio tikslo du gerai žinomi optimizavimo metodai ‐ genetiniai algoritmai ir atkaitinimo modeliavimo algoritmas ‐ buvo palyginti vidutinio dydžio (10 ir 15 poliu) pavyzdžiams išspresti. Tikslo funkcija imama didžiausia atraminI poliaus reakcija. Projektavimo kintamieji ‐ poliu koordinatIs. Atkaitinimo modeliavimo metodas laimi, todel jis buvo pritaikytas praktiniam uždaviniui (55 poliai) spresti. Spresti buvo naudojamas klasteris. Naujumas ‐ genetiniu algoritmu palyginimas su atkaitinimo modeliavimo metodu bei atkaitinimo modeliavimo metodo pritaikymas sprendžiant praktini uždavini.

ON THE PHYSICAL APPLICATION OF SIMULATED ANNEALING ALGORITHM

1999 ◽  
Vol 10 (06) ◽  
pp. 1065-1070 ◽  
Author(s):  
SHU-YOU LI ◽  
ZHI-HUI DU ◽  
MENG-YUE WU ◽  
JING ZHU ◽  
SAN-LI LI
Keyword(s):  
Simulated Annealing ◽  
Parameter Optimization ◽  
High Performance ◽  
Simulated Annealing Algorithm ◽  
Optimization Problems ◽  
Source Code ◽  
Physical Application ◽  
General Program ◽  
Annealing Algorithm

A high-performance general program is presented to deal with the multi-parameter optimization problems in physics. Considering the requirements of physical application, some small but significant modifications were made on the conventional simulated annealing algorithm. A parallel realization was suggested to further improve the performance of the program. Mathematical and physical examples were taken to test the feasibility and the efficiency of the program. The source code is available from the authors free of charge.

scholarly journals Experiences Using Hybrid MPI/OpenMP in the Real World: Parallelization of a 3D CFD Solver for Multi-Core Node Clusters

2010 ◽  
Vol 18 (3-4) ◽  
pp. 127-138 ◽  
Author(s):  
Gabriele Jost ◽  
Bob Robins
Keyword(s):  
Real World ◽  
High Performance ◽  
Programming Model ◽  
Hybrid Approach ◽  
Underwater Vehicles ◽  
Core Node ◽  
Real World Application ◽  
Hardware Platforms ◽  
Control Surfaces ◽  
Performance Computing

Today most systems in high-performance computing (HPC) feature a hierarchical hardware design: shared-memory nodes with several multi-core CPUs are connected via a network infrastructure. When parallelizing an application for these architectures it seems natural to employ a hierarchical programming model such as combining MPI and OpenMP. Nevertheless, there is the general lore that pure MPI outperforms the hybrid MPI/OpenMP approach. In this paper, we describe the hybrid MPI/OpenMP parallelization of IR3D (Incompressible Realistic 3-D) code, a full-scale real-world application, which simulates the environmental effects on the evolution of vortices trailing behind control surfaces of underwater vehicles. We discuss performance, scalability and limitations of the pure MPI version of the code on a variety of hardware platforms and show how the hybrid approach can help to overcome certain limitations.

scholarly journals Automated university lecture timetable using Heuristic Approach

2020 ◽  
Vol 39 (1) ◽  
pp. 1-14 ◽  
Author(s):  
A.M. Hambali ◽  
Y.A. Olasupo ◽  
M. Dalhatu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Heuristic Approach ◽  
Space Complexity ◽  
Tertiary Institution ◽  
Course Timetabling ◽  
Timetabling Problem ◽  
Hard Constraints ◽  
Course Timetabling Problem

There are different approaches used in automating course timetabling problem in tertiary institution. This paper present a combination of genetic algorithm (GA) and simulated annealing (SA) to have a heuristic approach (HA) for solving course timetabling problem in Federal University Wukari (FUW). The heuristic approach was implemented considering the soft and hard constraints and the survival for the fittest. The period and space complexity was observed. This helps in matching the number of rooms with the number of courses. Keywords: Heuristic approach (HA), Genetic algorithm (GA), Course Timetabling, Space Complexity.

scholarly journals A Two-Stage Three-Machine Flow Shop Assembly Problem Mixed with a Controllable Number and Sum-of-Processing Times-Based Learning Effect by Simulated Annealing Algorithms

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Shang-Chia Liu
Keyword(s):  
Simulated Annealing ◽  
Processing Time ◽  
Learning Effect ◽  
Flow Shop ◽  
Service Industries ◽  
Two Stage ◽  
Processing Times ◽  
Assembly Scheduling ◽  
Assembly Problem ◽  
Annealing Algorithms

The two-stage assembly scheduling problem is widely used in industrial and service industries. This study focuses on the two-stage three-machine flow shop assembly problem mixed with a controllable number and sum-of-processing times-based learning effect, in which the job processing time is considered to be a function of the control of the truncation parameters and learning based on the sum of the processing time. However, the truncation function is very limited in the two-stage flow shop assembly scheduling settings. Thus, this study explores a two-stage three-machine flow shop assembly problem with truncated learning to minimize the makespan criterion. To solve the proposed model, we derive several dominance rules, lemmas, and lower bounds applied in the branch-and-bound method. On the other hand, three simulated annealing algorithms are proposed for finding approximate solutions. In both the small and large size number of job situations, the SA algorithm is better than the JS algorithm in this study. All the experimental results of the proposed algorithm are presented on small and large job sizes, respectively.

High-Performance Solutions for Adaptive and Customizable Streaming of Interactive Content to Mobile Devices

2012 ◽  
pp. 154-180 ◽  
Author(s):  
Gianluca Paravati ◽  
Fabrizio Lamberti ◽  
Andrea Sanna ◽  
Cesare Celozzi
Keyword(s):  
Mobile Devices ◽  
High Performance ◽  
Delay Systems ◽  
Remote Visualization ◽  
Interactive Applications ◽  
Network Bandwidth ◽  
Low Delay ◽  
Hard Constraints ◽  
Recent Developments ◽  
And Control

Recent improvements in technology have opened new, intriguing, and challenging scenarios for the latest generation of mobile devices, and users are asking for an ever larger spectrum of applications. In particular, implementation of interactive applications is an exciting task. In spite of the continuous improvements in the hardware components of mobile devices, several applications are still based on the remote visualization paradigm that adopts streaming based solutions. Nevertheless, some interactive applications introduce hard constraints to be met when low-delay systems have to be designed. Moreover, these systems have to cope with unstable network bandwidth and limited device capabilities. This Chapter first reviews classic strategies to design and implement remote visualization architectures and then presents recent developments regarding high-performance solutions for streaming interactive and customizable contents to mobile devices. In particular, the newest techniques that are specifically able to efficiently cope with bandwidth fluctuations are discussed, and a comparison between optimization based and control based approaches is addressed.

Designing a Near Optimal Solution via Simulated Annealing for Dimensional Chain Assembly

2020 ◽  
pp. 330-336
Author(s):  
Chen-Kun Tsung ◽  
Hsuan-Yu Huang ◽  
Shu-Hui Yang ◽  
Po-Nien Tsou ◽  
Ming-Cheng Tsai ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Optimal Solution ◽  
Dimensional Chain

scholarly journals Computing the Assembly Guidance for Maximizing Product Quality in the Virtual Assembly

2020 ◽  
Vol 12 (11) ◽  
pp. 4690
Author(s):  
Chen-Kun Tsung ◽  
Tseng-Fung Ho ◽  
Hsuan-Yu Huang ◽  
Shu-Hui Yang ◽  
Po-Nien Tsou ◽  
...  
Keyword(s):  
Product Quality ◽  
Simulated Annealing Algorithm ◽  
Computation Time ◽  
Secondary Process ◽  
Assembly Lines ◽  
Solution Quality ◽  
Solution Property ◽  
Assembly Instructions ◽  
Assembly Guidance ◽  
Property Inheritance

Assembly is the final process of manufacturing, and a good assembly plan reduces the effect of the tolerance generated in the early stages by the tolerance elimination. In the current assembly lines, the assemblers pick up the workpieces and install them together by the assembly instructions. When the workpieces are oversize or undersize, the product can not be installed correctly. Therefore, the assembler considers the secondary processing to fix the tolerance and then installs them together again. The product could be installed, but the product quality may be reduced by the secondary process. So, we formulate the assembly process as a combinatorial optimization problem, named by the dimensional chain assembly (DCA) problem. Given some workpieces with the corresponding actual size, computing the assembly guidance is the goal of the DCA problem, and the product quality is applied to represent the solution quality. The assemblers follow the assembly guidance to install the products. We firstly prove that the DCA problem is NP-complete and collect the requirements of solving the DCA problem from the implementation perspective: the sustainability, the minimization of computation time, and the guarantee of product quality. We consider solution refinement and the solution property inheritance of the single-solution evolution approach to discover and refine the quality of the assembly guidance. Based on the above strategies, we propose the assembly guidance optimizer (AGO) based on the simulated annealing algorithm to compute the assembly guidance. From the simulation results, the AGO reaches all requirements of the DCA problem. The variance of the computation time and the solution quality is related to the problem scale linearly, so the computation time and the solution quality can be estimated by the problem scale. Moreover, increasing the search breadth is unnecessary for improving the solution quality. In summary, the proposed AGO satisfies with the necessaries of the sustainability, the minimization of computation time, and the guarantee of product quality for the requirements of the DCA, and it can be considered in the real-world applications.

scholarly journals AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)

2017 ◽  
Author(s):  
Marius Lindauer ◽  
Frank Hutter ◽  
Holger H. Hoos ◽  
Torsten Schaub
Keyword(s):  
High Performance ◽  
State Of The Art ◽  
The State ◽  
Problem Instance ◽  
Algorithm Selection ◽  
Algorithm Configuration ◽  
Optimal Values ◽  
Art Performance ◽  
The One

Algorithm selection (AS) techniques -- which involve choosing from a set of algorithms the one expected to solve a given problem instance most efficiently -- have substantially improved the state of the art in solving many prominent AI problems, such as SAT, CSP, ASP, MAXSAT and QBF. Although several AS procedures have been introduced, not too surprisingly, none of them dominates all others across all AS scenarios. Furthermore, these procedures have parameters whose optimal values vary across AS scenarios. In this extended abstract of our 2015 JAIR article of the same title, we summarize AutoFolio, which uses an algorithm configuration procedure to automatically select an AS approach and optimize its parameters for a given AS scenario. AutoFolio allows researchers and practitioners across a broad range of applications to exploit the combined power of many different AS methods and to automatically construct high-performance algorithm selectors. We demonstrate that AutoFolio was able to produce new state-of-the-art algorithm selectors for 7 well-studied AS scenarios and matches state-of-the-art performance statistically on all other scenarios. Compared to the best single algorithm for each AS scenario, AutoFolio achieved average speedup factors between 1.3 and 15.4.

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