Novel Form-Finding of Tensegrity Structures Using Ant Colony Systems

2011 ◽  
Author(s):  
Yao Chen ◽  
Jian Feng ◽  
Yongfen Wu
Keyword(s):  
Travelling Salesman Problem ◽  
Ant Colony ◽  
Ant Colony System ◽  
Form Finding ◽  
Tensegrity Structures ◽  
Connectivity Patterns ◽  
Feasible Solutions ◽  
Ant Colony Systems ◽  
The Given

Tensegrity structures are drawing the attention of architects and engineers due to their remarkable configurations. They have inextensional mechanisms, yet they are stable. The determination of connectivity patterns of the compression bars and tension cables is a key to design tensegrity structures. In this paper, a discrete optimization model for the form-finding of tensegrity structures was developed, and converted into a modified travelling salesman problem (TSP). The ant colony system (ACS) was used to search for feasible solutions, where all the given nodes were taken as different cities in the network. To obtain optimized shapes of tensegrity structures with stable equilibriums and adequate stiffness, an objective function was introduced. Examples based on the geometries of some polyhedra were carried out using the proposed technique. Many different configurations of the assemblies which consist of cables and bars are transformed into interesting tensegrity structures. It concludes that this novel algorithm could be applicable to the form-finding of both regular and nonregular tensegrity structures.

Novel Form-Finding of Tensegrity Structures Using Ant Colony Systems

2012 ◽  
Vol 4 (3) ◽  
Author(s):  
Yao Chen ◽  
Jian Feng ◽  
Yongfen Wu
Keyword(s):  
Ant Colony ◽  
Physical Models ◽  
Ant Colony System ◽  
Form Finding ◽  
Tensegrity Structures ◽  
Stress States ◽  
Feasible Solutions ◽  
The Stability ◽  
Ant Colony Systems ◽  
External Loads

Tensegrity structures have remarkable configurations and are drawing the attention of architects and engineers. They possess inextensional mechanisms and self-stress states at a static equilibrium configuration under no external loads. For geometry with its nodes fixed, different connectivity patterns of the compression bars and tension cables might bring some novel tensegrity structures. Thus, form-finding is the key to designing novel tensegrity structures. Here, we develop a discrete optimization model for the form-finding and convert it into a modified traveling salesman problem (TSP). The ant colony system (ACS) is used to search for feasible solutions, where all the predetermined nodes are taken as different cities in the network. An objective function that considers the stability and the relative stiffness is developed to obtain the optimized configurations of tensegrity structures. Examples based on some regular geometries (including a hexagon and two polyhedra) and two nonregular geometries are carried out using the proposed technique. Many different configurations of the pin-jointed assemblies are transformed into interesting tensegrity structures. To verify the proposed method, some physical models are constructed and compared to the tensegrity structures obtained from the form-finding process. We conclude that this novel algorithm can be applicable to the form-finding of both regular and nonregular tensegrity structures.

scholarly journals STUDY AND APPLY ACO ALGORITHM IN TIME-COST OPTIMIZATION OF CONSTRUCTION PROJECT

2010 ◽  
Vol 13 (1) ◽  
pp. 17-30
Author(s):  
Luan Hong Pham ◽  
Nhan Thanh Duong
Keyword(s):  
Cost Optimization ◽  
Construction Project ◽  
Heuristic Method ◽  
Ant Colony ◽  
Ant Colony System ◽  
Time Cost ◽  
Project Duration ◽  
Proposed Model ◽  
Feasible Solutions ◽  
Computational Resources

Time-cost optimization problem is one of the most important aspects of construction project management. In order to maximize the return, construction planners would strive to optimize the project duration and cost concurrently. Over the years, many researches have been conducted to model the time-cost relationships; the modeling techniques range from the heuristic method and mathematical approach to genetic algorithm. In this paper, an evolutionary-based optimization algorithm known as ant colony optimization (ACO) is applied to solve the multi-objective time-cost problem. By incorporating with the modified adaptive weight approach (MAWA), the proposed model will find out the most feasible solutions. The concept of the ACO-TCO model is developed by a computer program in the Visual Basic platforms. An example was analyzed to illustrate the capabilities of the proposed model and to compare against GA-based TCO model. The results indicate that ant colony system approach is able to generate better solutions without making the most of computational resources which can provide a useful means to support construction planners and managers in efficiently making better time-cost decisions.

scholarly journals Travel route scheduling based on user’s preferences using simulated annealing

2019 ◽  
Vol 9 (2) ◽  
pp. 1275 ◽  
Author(s):  
Z. K. A. Baizal ◽  
Kemas M. Lhaksmana ◽  
Aniq A. Rahmawati ◽  
Mizanul Kirom ◽  
Zidni Mubarok
Keyword(s):  
Simulated Annealing ◽  
Average Length ◽  
Travelling Salesman Problem ◽  
Ant Colony ◽  
Routine Activity ◽  
Tourist Destination ◽  
Route Scheduling ◽  
Annealing Method ◽  
Length Of Visit

<p>Nowadays, traveling has become a routine activity for many people, so that many researchers have developed studies in the tourism domain, especially for the determination of tourist routes. Based on prior work, the problem of determining travel route is analogous to finding the solution for travelling salesman problem (TSP). However, the majority of works only dealt with generating the travel route within one day and also did not take into account several user’s preference criteria. This paper proposes a model for generating a travel route schedule within a few days, and considers some user needs criteria, so that the determination of a travel route can be considered as a multi-criteria issue. The travel route is generated based on several constraints, such as travel time limits per day, opening/closing hours and the average length of visit for each tourist destination. We use simulated annealing method to generate the optimum travel route. Based on evaluation result, the optimality of the travel route generated by the system is not significantly different with ant colony result. However, our model is far more superior in running time compared to Ant Colony method.</p>

Post-Disassembly Part-Machine Clustering Using Artificial Neural Networks and Ant Colony Systems

2013 ◽  
pp. 135-150 ◽  
Keyword(s):  
Complex Problem ◽  
Ant Colony ◽  
System Structure ◽  
Ant Colony System ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Reusable Components ◽  
Clustering Problem ◽  
Ant Colony Systems

After transhipment, the remanufacturable parts/components are usually released to the reprocessing facility where the necessary operations (such as disassembly) are performed. At times, formation of parts/components for reprocessing operations is a complex problem with broad implications to an organization, both on system structure and system operations. The chapter starts with an introduction about the issue of the classification of disassembled and reusable components. Then the related studies dealing with similar problems in the literature are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. The authors formulate the problem as a part-machine clustering problem in which, according to similarities of reprocessing requirement, disassembled parts/components are grouped into families, and machines are organized as cells. A detailed description about the approach (i.e., adaptive resonance theory neural network and ant colony system) can be found in the proposed methodology section. Right after this, two illustrative examples are explained in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Study on the Sky Luminance Distribution of Information Methods by Ant Colony Systems

2011 ◽  
Vol 48-49 ◽  
pp. 1202-1207 ◽  
Author(s):  
Ying He ◽  
Ping Guo ◽  
Yong Lin
Keyword(s):  
Lighting Design ◽  
Ant Colony ◽  
Distribution Model ◽  
Ant Colony System ◽  
Standard Work ◽  
Luminance Distribution ◽  
Easy Calculation ◽  
Complex Optimization ◽  
Ant Colony Systems ◽  
Calculation Software

The sky luminance distribution model studied by information methods use a new arithmetic to solve complex optimization heuristic algorithm, ant colony system. Through analyzing and optimizing the effect factors of sky luminance by the ant colony system, the study got the coefficients value of sky relative luminance distribution numerical expressions. Based on the study, develop a set of convenient and practical sky luminance model calculation software, which can provide an intuitive and easy calculation. This model has higher precision. It provides valuable results for day lighting using, especially high precise and standard work of day lighting design both in theory and application.

Solution of Travelling Salesman Problem Using Ant Colony Algorithm

2014 ◽  
Vol 548-549 ◽  
pp. 1206-1212
Author(s):  
Sevda Dayıoğlu Gülcü ◽  
Şaban Gülcü ◽  
Humar Kahramanli
Keyword(s):  
Discrete Optimization ◽  
Ant Colony Algorithm ◽  
Optimization Problems ◽  
Travelling Salesman Problem ◽  
Heuristic Method ◽  
Ant Colony ◽  
Ant Colony System ◽  
Travelling Salesman ◽  
Ant Colonies ◽  
Discrete Optimization Problems

Recently some studies have been revealed by inspiring from animals which live as colonies in the nature. Ant Colony System is one of these studies. This system is a meta-heuristic method which has been developed based upon food searching characteristics of the ant colonies. Ant Colony System is applied in a lot of discrete optimization problems such as travelling salesman problem. In this study solving the travelling salesman problem using ant colony system is aimed.

Form-finding of free-form tensegrity structures by genetic algorithm–based total potential energy minimization

2016 ◽  
Vol 20 (5) ◽  
pp. 784-796 ◽  
Author(s):  
Fatih Uzun
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Free Form ◽  
Stable Form ◽  
Equilibrium Form ◽  
Form Finding ◽  
Tensegrity Structures ◽  
Computational Performance ◽  
Stability Of Structures

Free-form tensegrities are composed of randomly connected cable and strut elements. The complexity of these structures causes determination of their self-equilibrium form to be a formidable task. There can be an infinite number of solutions with different forms, but it is difficult to identify the best form in terms of stability. Based on the fact that stability of structures is inversely proportional to potential energy, a genetic algorithm minimization process is developed to determine the self-equilibrium form of free-form regular tensegrity structures. The capability of the form-finding process on determination of the most stable form with minimum potential energy is investigated using two main parameters of free-form regular tensegrities which are cable–strut length ratio at rest and number of strut elements. The computational performance of the proposed method is also tested using free-form tensegrities with different number of structural elements.

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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