An evolutionary simulated annealing algorithm for optimizing robotic task point ordering

Barral, D.; Perrin, Jean-Pierre; Dombre, Etienne; Liégeois, A.

doi:10.1109/isatp.1999.782952

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…If city1 < city2, P is set by formula (5). Otherwise P is set by formula (6). Where the new solution is P = c 1 c 2 c n .…”

Section: An Effective Sa Algorithm For the Tspmentioning

confidence: 99%

“…At the same time, the TSP is an NP-complete problem, 14 whose computational complexity rises exponentially with the input size. Hence, it is advantageous to find suboptimal solutions with a reasonable cost in many of TSP applications such as vehicle routing, 9 data transmission in computer networks, 13 image processing and pattern recognition, 5 robot navigation, 6 and drilling problem. 8 The TSP can be understood as a search for the shortest closed tour that visits each city once and only once.…”

Section: Introductionmentioning

confidence: 99%

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An Effective Simulated Annealing Algorithm for Solving the Traveling Salesman Problem

Wang¹,

Geng²,

Shao³

2009

Jnl of Comp & Theo Nano

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It is well known that the traveling salesman problem (TSP) is one of the most studied NP-complete problems, and evolutionary technique such as simulated annealing has mostly been used to solve various NP-complete problems. In this paper, a two-stage simulated annealing (two-stage SA) algorithm is proposed to solve the TSP, and the two-stage SA algorithm is made up of two stages. In the first stage, a simple simulated annealing (simple SA) algorithm is proposed to obtain some appropriate solutions or closed tours. In the second stage, an effective simulated annealing (effective SA) algorithm is proposed to obtain solutions with good quality based on the solutions or closed tours obtained by the simple SA algorithm. To assess the effectiveness of the two-stage SA algorithm, simulations were carried out on 23 benchmark TSP instances. The simulation results show that the two-stage SA algorithm can obtain solutions with better quality than four recent algorithms such as ant colony optimization algorithm, self-organizing maps algorithm, particle swarm optimization algorithm and constructive optimizer neural network algorithm.

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“…If city1 < city2, P is set by formula (5). Otherwise P is set by formula (6). Where the new solution is P = c 1 c 2 c n .…”

Section: An Effective Sa Algorithm For the Tspmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Effective Simulated Annealing Algorithm for Solving the Traveling Salesman Problem

Wang¹,

Geng²,

Shao³

2009

Jnl of Comp & Theo Nano

View full text Add to dashboard Cite

show abstract

“…The aim of this research is to seek for an effective and efficient algorithm to optimise the design of curved roof surface. Some research has demonstrated the benefits of an evolutionary SA algorithm in searching for an optimal result (Barral et al, 1999;Loomis, 2001Loomis, , 2004. As genetic algorithm (GA) can offer designers a relatively quick means of identifying a selection of good solutions (Rafiq et al, 2003), it is expected to employ GA to make up the drawback of current algorithms built in the CATIA system.…”

Section: Introductionmentioning

confidence: 99%

Optimization of curved roof surface design using GA

Guo

Kong

et al. 2012

Journal of Engineering, Design and Technology

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Purpose -Due to the increasing complexity of curved roof surface design and the inadequate optimisation algorithms in design software, the optimisation of curved roof surface design needs to be studied further. The purpose of this paper is to develop an alternative approach to improve the efficiency and effectiveness of curved roof surface design of buildings. Design/methodology/approach -To achieve the purpose, an optimisation method/tool is developed through reviewing the application of CATIA and integrating genetic algorithm with CATIA; and the effectiveness to perform the GA-based optimisation method is demonstrated by using a real-life case study. Furthermore, a comparison among different optimisation algorithms currently available in the CATIA system is conducted. Findings -Through the case study and the comparison, it is found that the GA-based method can improve the performance of optimisation for curved roof surface design in the CATIA system; however, further research work is required for the best global optimisation result. Originality/value -The paper proposes an optimisation method for curved roof surface design through integrating genetic algorithm with CATIA. This method improves the current method of curved roof surface design.

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An Extended Self-Organizing Map based on 2-opt algorithm for solving symmetrical Traveling Salesperson Problem

Ahmad

Kim

2014

Neural Comput & Applic

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An evolutionary simulated annealing algorithm for optimizing robotic task point ordering

Cited by 6 publications

References 15 publications

An Effective Simulated Annealing Algorithm for Solving the Traveling Salesman Problem

An Effective Simulated Annealing Algorithm for Solving the Traveling Salesman Problem

Optimization of curved roof surface design using GA

An Extended Self-Organizing Map based on 2-opt algorithm for solving symmetrical Traveling Salesperson Problem

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