Minimum cost topology optimisation of ATM networks using genetic algorithms

2000 ◽  
Vol 36 (24) ◽  
pp. 2051 ◽  
Author(s):  
H. Sayoud ◽  
K. Takahashi ◽  
B. Vaillant
Keyword(s):  
Genetic Algorithms ◽  
Minimum Cost ◽  
Atm Networks ◽  
Topology Optimisation

A Genetic Algorithm for Cost Estimating Turned Parts in an Interactive DFM Environment

2003 ◽  
Author(s):  
R. Sebastian Schrader ◽  
Michael L. Philpott ◽  
Gautam Subbarao ◽  
Dale E. Holmes
Keyword(s):  
Genetic Algorithms ◽  
Initial Conditions ◽  
Cost Minimization ◽  
Optimization Technique ◽  
Minimum Cost ◽  
Cutting Parameters ◽  
Replacement Policy ◽  
Total Production ◽  
Machining Parameters ◽  
Tool Replacement

This paper presents a method for the optimization of machining parameters, essential for the determination of an economical operating point for multi-pass turning operations. Optimal selection of cutting parameters such as the number of passes, depth of cuts, cutting speeds and feed rates are critical to process planning and cost optimization. This in turn creates a crossing point between product design and manufacturing. Generally, machining models are complex since they are highly non-linear. This research utilizes genetic algorithms as an optimization technique in order to maximize the accuracy of results, the computational achievement, and to minimize the influence of initial conditions and part geometry. A new approach that uses conventional turning process modeling along with genetic algorithms to rapidly search and optimize the feasible workspace is considered. The total production cost minimization is achieved by adding together the minimum cost of each roughing pass and the final finishing pass. In addition, the preventive tool replacement policy used in practice is incorporated. Finally, the results obtained for test cases are evaluated and compared.

scholarly journals Optimum Design of Pile Foundation by Automatic Grouping Genetic Algorithms

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaofeng Liu ◽  
Gengdong Cheng ◽  
Bo Wang ◽  
Shuzhi Lin
Keyword(s):  
Genetic Algorithms ◽  
Cost Optimization ◽  
Minimum Cost ◽  
Design Stage ◽  
Cardinality Constraint ◽  
Design Constraints ◽  
Concurrent Optimization ◽  
Modular Method ◽  
Automatic Grouping ◽  
Pile Length

This paper studies the optimum conceptual design of pile foundations at the initial design stage. A modular method is proposed, which divides the foundation into modules and each module is identified by its characteristics of pile length, diameter, number and layout. Modules with the same characteristics may be packed and represented by a design variable. A minimum-cost optimization model with multiple design constraints based on Chinese code and a cardinality constraint is built to achieve the concurrent optimization of pile size and layout. The model is solved by the improved automatic grouping genetic algorithms to obtain the design with optimal variables and optimal variable grouping. A practical example demonstrates the effectiveness of the proposed approach.

scholarly journals Optimizing Capacity Assignment in Multiservice MPLS Networks

2017 ◽  
Vol 29 (1) ◽  
Author(s):  
Abdoul Rassaki ◽  
Andre Nel
Keyword(s):  
Programming Model ◽  
Minimum Cost ◽  
Lagrangean Relaxation ◽  
Telecommunication Networks ◽  
Common Trunk ◽  
Topology Optimisation ◽  
Capacity Assignment ◽  
Optimum Selection ◽  
Flow Assignment ◽  
Experimental Findings

The general Multiprotocol Label Switch (MPLS) topology optimisation problem is complex and concerns the optimum selection of links, the assignment of capacities to these links and the routing requirements on these links. Ideally, all these are jointly optimised, leading to a minimum cost network which continually meets given objectives on network delay and throughput. In practice, these problems are often dealt with separately and a solution iterated. In this paper, we propose an algorithm that computes the shortest routes, assigns optimal flows to these routes and simultaneously determines optimal link capacities. We take into account the dynamic adaptation of optimal link capacities by considering the same Quality of Service (QoS) measure used in the flow assignment problem in combination with a blocking model for describing call admission controls (CAC) in multiservice broadband telecommunication networks. The main goal is to achieve statistical multiplexing advantages with multiple traffic and QoS classes of connections that share a common trunk present. We offer a mathematical programming model of the problem and proficient solutions which are founded on a Lagrangean relaxation of the problem. Experimental findings on 2-class and 6-class models are reported.

Fuzzy logic tool and genetic algorithms for CAC in ATM networks

1996 ◽  
Vol 32 (11) ◽  
pp. 973 ◽  
Author(s):  
M.F. Ramalho ◽  
E.M. Scharf
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Atm Networks

Bandwidth-demand prediction in virtual path in ATM networks using genetic algorithms

1999 ◽  
Vol 22 (12) ◽  
pp. 1127-1135 ◽  
Author(s):  
N. Swaminathan ◽  
J. Srinivasan ◽  
S.V. Raghavan
Keyword(s):  
Genetic Algorithms ◽  
Atm Networks ◽  
Virtual Path ◽  
Demand Prediction ◽  
Bandwidth Demand

Study on the Synthesis Optimization of Time-Cost-Climate in Project

2014 ◽  
Vol 687-691 ◽  
pp. 4918-4921
Author(s):  
Dao Hong Wei ◽  
Hou Gui Zhou
Keyword(s):  
Genetic Algorithms ◽  
Influence Factors ◽  
Minimum Cost ◽  
Control Model ◽  
Time Cost ◽  
Schedule Control ◽  
Start Time ◽  
Working Procedure ◽  
The Impact ◽  
Minimum Costs

For influence factors to engineering progress in project management of fund, resource allocation and climate etc, establish a schedule control model under the minimum cost. Using genetic algorithms for analysis, obtained the earliest start time of each working procedure at minimum costs. This method can avoid the impact of human factors and provides the powerful theory support for the policy-maker.

scholarly journals Using Genetic Algorithms for Hardware Core Placement and Mapping in NoC-Based Reconfigurable Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Jonas Gomes Filho ◽  
Marius Strum ◽  
Wang Jiang Chau
Keyword(s):  
Genetic Algorithms ◽  
Global Minimum ◽  
Minimum Cost ◽  
Reconfigurable Systems ◽  
Placement Problem ◽  
Communication Structure ◽  
Irregular Networks ◽  
Problem Formalization ◽  
Reconfigurable Device ◽  
Important Activity

Mapping of cores has been an important activity in NoC-based system design aimed to find the best topological location onto the NoC, such that the metrics of interest can be greatly optimized. In the last years, partial reconfigurable systems (PRSs) have included Networks-on-Chips (NoCs) as their communication structure, adding complexity to the problem of mapping. Several works have proposed specific and robust NoC architectures for PRSs, forming indirect and irregular networks, in which cases the mapping and placement problems must be treated altogether. The placement deals with the physical positioning of those cores inside the reconfigurable device. Up to now, to the best of our knowledge, the mapping-placement problem for those kinds of architectures has not been addressed yet. In this work, the problem formalization for the design-time hardware core placement and mapping in PRS-NoCs is proposed and methodologies for solving it with genetic algorithms (GAs) are presented. Several GA crossovers and methodologies are compared for obtaining the best solution. Results have shown that best GA solution obtained, in average, communication costs with 4% of penalty when compared with global minimum cost, obtained in a semiexhaustive approach. In addition, the algorithm presents low execution times.

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