Multi-Objective Topology Design of Industrial Ethernet Networks

Frequenz ◽  
2012 ◽  
Vol 66 (5-6) ◽  
Author(s):  
Lei Zhang ◽  
Mattias Lampe ◽  
Zhi Wang
Keyword(s):  
Network Performance ◽  
Search Algorithm ◽  
Design Method ◽  
High Reliability ◽  
Industrial Applications ◽  
Topology Design ◽  
Variable Neighbourhood Search ◽  
Industrial Ethernet ◽  
Multi Objective ◽  
Ethernet Networks

AbstractThe objective of this paper is to investigate methods to guarantee the network performance of industrial Ethernet networks by an optimized topology design. The proposed approach differs from former works on network design by taking into account the specific requirements of industrial applications, the Quality of Service (QoS) related features of industrial Ethernet protocols, and the increasing network complexity in the industrial field. A multi-objective variable neighbourhood search algorithm (MOVNS) is presented offering a co-design method of physical topology and logical topology to satisfy the requirements of real-time capability, high reliability, and fast recovery time. The result analysis on simulation test cases shows the proposed algorithm can greatly improve the performance of industrial Ethernet networks at a moderate computational complexity.

An Irregular Topology Generation Using Power-Interference Co-Optimization for Hybrid Application-Specific Wireless NoC

2017 ◽  
Vol 27 (03) ◽  
pp. 1850036
Author(s):  
Jianhua Li ◽  
Ning Wu ◽  
Yongliang Hu ◽  
Gaobiao Wu
Keyword(s):  
Power Efficiency ◽  
Optimization Design ◽  
Resource Constraints ◽  
Search Algorithm ◽  
Design Method ◽  
Collaborative Optimization ◽  
Topology Design ◽  
Silicon Area ◽  
Heuristic Search Algorithm ◽  
Application Specific

Aiming at the efficient topology design of upper-layer network in hybrid application-specific wireless Network-on-Chip (NoC), we propose a new design method of power-interference collaborative optimization (PICO) after analyzing the potential factors of high power consumption and interference, and establishing relevant mathematical model. The design method is used for generating optimal irregular topology of ultralow power-interference using effective wireless link placement and channel assignment based on heuristic search algorithm under certain signal-to-interference plus noise ratio and strict resource constraints, such as the available number of wireless links and silicon area. In addition, the traffic balance between channels is carefully considered in the topology optimization. The theoretical calculation and cycle-accurate simulation results demonstrate that the resulting irregular topology generated by the co-optimization design method outperforms the conventional counterparts in terms of achievable throughput, power efficiency and bandwidth.

Research on Intelligent Design Method of Ship Cabin Layout

2020 ◽  
Vol 54 (2) ◽  
pp. 79-92
Author(s):  
Yun-long Wang ◽  
Zhang-pan Wu ◽  
Guan Guan ◽  
Chao-guang Jin
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Intelligent Design ◽  
Search Algorithm ◽  
Design Method ◽  
Optimal Solution ◽  
Location Model ◽  
Improved Genetic Algorithm ◽  
Multi Objective ◽  
Constraint Model

AbstractThe design of the ship cabin layout is a multi-objective comprehensive optimization problem, which needs to consider the location of the passage, cabin layout, space utilization ratio, functional realization, comfort, safety, and so on. In this paper, an improved tabu-criterion genetic algorithm for the intelligent design of ship cabin layout is proposed. According to the characteristics of ship accommodation cabin layout design, a ship deck layout area model and a multi-objective optimization model including relative location model, absolute location model, and ergonomic constraint model are established. The neighborhood transformation criterion and tabu-criterion of tabu search algorithm are introduced into genetic algorithm to advance the local search ability of a genetic algorithm. At the same time, a new genetic algorithm coding method is proposed to avoid the generation of illegal solutions in cabin layout sequence crossover and mutation operation. The improved genetic algorithm can effectively improve the local search ability of a genetic algorithm and make the algorithm converge to the optimal solution as soon as possible at the later stage of calculation. Finally, the simulation results verify the feasibility and efficiency of the proposed intelligent design method for ship accommodation cabin layout.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Voltage Stability Enhancement with Optimal Placement of IPFC

2019 ◽  
Vol 8 (4) ◽  
pp. 9465-9471
Keyword(s):  
Transmission Line ◽  
Objective Function ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Test System ◽  
Optimal Location ◽  
Optimal Placement ◽  
Utilization Factor ◽  
Location Selection ◽  
Multi Objective

This paper presents a novel technique based on Cuckoo Search Algorithm (CSA) for enhancing the performance of multiline transmission network to reduce congestion in transmission line to huge level. Optimal location selection of IPFC is done using subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of real power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing transmission line congestion is obtained. The simulation is performed using MATLAB for IEEE 30-bus test system. The performance of CSA has been considered for various loading conditions. Results shows that the proposed CSA technique performs better by optimal location of IPFC while maintaining power system performance

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