Different types of stability of vector integer optimization problem: General approach

2008 ◽  
Vol 44 (3) ◽  
pp. 429-433 ◽  
Author(s):  
T. T. Lebedeva ◽  
T. I. Sergienko
Keyword(s):  
Optimization Problem ◽  
Integer Optimization ◽  
Different Types

scholarly journals Optimization Issues of a Hammer Mill Working Process Using Statistical Modelling

2021 ◽  
Vol 13 (2) ◽  
pp. 973
Author(s):  
Gigel Paraschiv ◽  
Georgiana Moiceanu ◽  
Gheorghe Voicu ◽  
Mihai Chitoiu ◽  
Petru Cardei ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Optimization Problem ◽  
Specific Energy Consumption ◽  
Statistical Modelling ◽  
Hammer Mill ◽  
Objective Functions ◽  
Working Process ◽  
Rotor Spinning ◽  
Milled Material ◽  
Different Types

Our paper presents the hammer mill working process optimization problem destined for milling energetic biomass (MiscanthusGiganteus and Salix Viminalis). For the study, functional and constructive parameters of the hammer mill were taken into consideration in order to reduce the specific energy consumption. The energy consumption dependency on the mill rotor spinning frequency and on the sieve orifices in use, as well as on the material feeding flow, in correlation with the vegetal biomass milling degree was the focus of the analysis. For obtaining this the hammer mill was successively equipped with 4 different types of hammers that grind the energetic biomass, which had a certain humidity content and an initial degree of reduction ratio of the material. In order to start the optimization process of hammer mill working process, 12 parameters were defined. The objective functions which minimize hammer mill energy consumption and maximize the milled material percentage with a certain specific granulation were established. The results obtained can serve as the basis for choosing the optimal working, constructive, and functional parameters of hammer mills in this field, and for a better design of future hammer mills.

Loss reduction as a Mixed Integer optimization problem

2009 ◽  
Author(s):  
Stephane Fliscounakis ◽  
Fabrice Zaoui ◽  
Marie-Pierre Houry ◽  
Emilie Milin
Keyword(s):  
Optimization Problem ◽  
Mixed Integer ◽  
Loss Reduction ◽  
Integer Optimization ◽  
Mixed Integer Optimization

scholarly journals An Instance Data Repository for the Round-robin Sports Timetabling Problem

2020 ◽  
Vol 45 (2) ◽  
pp. 184-200
Author(s):  
David Van Bulck ◽  
Dries Goossens ◽  
Jo¨rn Scho¨nberger ◽  
Mario Guajardo
Keyword(s):  
Optimization Problem ◽  
Real Life ◽  
Short Description ◽  
Problem Instance ◽  
Data Repository ◽  
Timetabling Problem ◽  
Classification Framework ◽  
Different Types ◽  
Problem Instances ◽  
Complex Matter

The sports timetabling problem is a combinatorial optimization problem that consists of creating a timetable that defines against whom, when and where teams play games. This is a complex matter, since real-life sports timetabling applications are typically highly constrained. The vast amount and variety of constraints and the lack of generally accepted benchmark problem instances make that timetable algorithms proposed in the literature are often tested on just one or two specific seasons of the competition under consideration. This is problematic since only a few algorithmic insights are gained. To mitigate this issue, this article provides a problem instance repository containing over 40 different types of instances covering artificial and real-life problem instances. The construction of such a repository is not trivial, since there are dozens of constraints that need to be expressed in a standardized format. For this, our repository relies on RobinX, an XML-supported classification framework. The resulting repository provides a (non-exhaustive) overview of most real-life sports timetabling applications published over the last five decades. For every problem, a short description highlights the most distinguishing characteristics of the problem. The repository is publicly available and will be continuously updated as new instances or better solutions become available.

Optimization of Radial Cams with Translating Roller Follower through Genetic Algorithms

2015 ◽  
Vol 783 ◽  
pp. 83-94
Author(s):  
Alberto Borboni
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Contact Pressure ◽  
Optimization Problem ◽  
Optimization Method ◽  
Optimization Process ◽  
Radius Of Curvature ◽  
Design Problems ◽  
Computational Optimization ◽  
Different Types

In this work, the optimization problem is studied for a planar cam which rotates around its axis and moves a centered translating roller follower. The proposed optimization method is a genetic algorithm. The paper deals with different design problems: the minimization of the pressure angle, the maximization of the radius of curvature and the minimization of the contact pressure. Different types of motion laws are tested to found the most suitable for the computational optimization process.

An adaptive cuckoo optimization algorithm for system design optimization under failure dependencies

2019 ◽  
Vol 233 (6) ◽  
pp. 1099-1105 ◽  
Author(s):  
Mohamed Arezki Mellal ◽  
Enrico Zio
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Strong Dependence ◽  
Integer Optimization ◽  
System Availability ◽  
Cuckoo Optimization Algorithm ◽  
Availability Constraint ◽  
System Design Optimization ◽  
Minimum System

This article presents an algorithm for optimal redundancy and repair team allocation with respect to minimum system cost and a system availability constraint. Four scenarios are considered for the failures occurring in the subsystems of the system: independence, linear dependence, weak dependence, and strong dependence. An adaptive cuckoo optimization algorithm is developed for solving the nonlinear integer optimization problem of allocation. A series–parallel system with six subsystems is considered as a case study for demonstration purposes. The results obtained highlight the good performance of the developed algorithm.

scholarly journals Spectral Clustering in Heterogeneous Information Networks

2019 ◽  
Vol 33 ◽  
pp. 4221-4228 ◽  
Author(s):  
Xiang Li ◽  
Ben Kao ◽  
Zhaochun Ren ◽  
Dawei Yin
Keyword(s):  
Spectral Clustering ◽  
Optimization Problem ◽  
Clustering Algorithms ◽  
Similarity Matrix ◽  
Heterogeneous Information ◽  
Heterogeneous Information Networks ◽  
Clustering Quality ◽  
Different Types ◽  
Meta Path ◽  
Matrix Construction

A heterogeneous information network (HIN) is one whose objects are of different types and links between objects could model different object relations. We study how spectral clustering can be effectively applied to HINs. In particular, we focus on how meta-path relations are used to construct an effective similarity matrix based on which spectral clustering is done. We formulate the similarity matrix construction as an optimization problem and propose the SClump algorithm for solving the problem. We conduct extensive experiments comparing SClump with other state-of-the-art clustering algorithms on HINs. Our results show that SClump outperforms the competitors over a range of datasets w.r.t. different clustering quality measures.

Forced Response Reduction of a Blisk by Means of Intentional Mistuning

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Bernd Beirow ◽  
Arnold Kühhorn ◽  
Felix Figaschewsky ◽  
Alfons Bornhorn ◽  
Oleg V. Repetckii
Keyword(s):  
Optimization Problem ◽  
Negative Impact ◽  
Forced Response ◽  
Reduced Order Models ◽  
Integer Optimization ◽  
Safe Operation ◽  
Reduced Order ◽  
Aerodynamic Damping ◽  
Influence Coefficients ◽  
Engine Order

The effect of intentional mistuning has been analyzed for an axial turbocharger blisk with the objective of limiting the forced response due to low engine order excitation (LEO). The idea behind the approach was to increase the aerodynamic damping for the most critical fundamental mode in a way that a safe operation is ensured without severely losing aerodynamic performance. Apart from alternate mistuning, a more effective mistuning pattern is investigated, which has been derived by means of optimization employing genetic algorithms. In order to keep the manufacturing effort as small as possible, only two blade different geometries have been allowed, which means that an integer optimization problem has been formulated. Two blisk prototypes have been manufactured for purpose of demonstrating the benefit of the intentional mistuning pattern identified in this way: A first one with and a second one without employing intentional mistuning. The real mistuning of the prototypes has been experimentally identified. It is shown that the benefit regarding the forced response reduction is retained in spite of the negative impact of unavoidable additional mistuning due to the manufacturing process. Independently, further analyzes have been focused on the robustness of the solution by considering increasing random structural mistuning and aerodynamic mistuning as well. The latter one has been modeled by means of varying aerodynamic influence coefficients (AIC) as part of Monte Carlo simulations. Reduced order models have been employed for these purposes.

scholarly journals An Algorithm for Rescheduling of Trains under Planned Track Closures

2021 ◽  
Vol 11 (5) ◽  
pp. 2334
Author(s):  
Grzegorz Filcek ◽  
Dariusz Gąsior ◽  
Maciej Hojda ◽  
Jerzy Józefczyk
Keyword(s):  
Optimization Problem ◽  
Broad Class ◽  
Mixed Integer ◽  
Time Shift ◽  
Integer Optimization ◽  
Train Rescheduling ◽  
Feasible Solutions ◽  
The Given ◽  
Np Hardness

This work considered a joint problem of train rescheduling and closure planning. The derivation of a new train run schedule and the determination of a closure plan not only must guarantee the satisfaction of all the given constraints but also must optimize the number of accepted closures, the number of approved train runs, and the total time shift between the resultant and the original schedule. Presented is a novel nonlinear mixed integer optimization problem which is valid for a broad class of railway networks. A multi-level hierarchical heuristic algorithm is introduced due to the NP-hardness of the considered optimization problem. The algorithm is able, on an iterative basis, to jointly select closures and train runs, along with the derivation of a train schedule. Results obtained by the algorithm, launched for the conducted experiments, confirm its ability to provide acceptable and feasible solutions in a reasonable amount of time.

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