The design of the global navigation satellite system surveying networks using genetic algorithms

Saleh, Hussain; Chelouah, Rachid

doi:10.1016/j.engappai.2003.11.001

Cited by 65 publications

(40 citation statements)

References 9 publications

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“…It can be said that optimal network design problems have been considered by surveyors ever since their inception, when most networks were designed based on surveyors' intuition or experience. With the development of modern computer technologies, the design approaches have evolved from the empirical methods (Asplund, 1963), through analytical methods (Kuang, 1996;Schmitt, 1985a and1985b), to some well-known heuristic methods, e.g., simulated annealing (Baselga, 2011;Metropolis et al, 1953), genetic algorithms (Holland, 1975;Saleh et al, 2004), and particle swarm optimization (Doma and Sedeek, 2014;Kennedy, 2011), whose principles are inspired by many adaptive optimization phenomena in nature.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization in Optimal First-Order Design of Indoor TLS Networks

Jia

Lichti

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The optimal network design problem has been well addressed in geodesy and photogrammetry but has not received the same attention for terrestrial laser scanner (TLS) networks. The goal of this research is to develop a complete design system that can automatically provide an optimal plan for high-accuracy, large-volume scanning networks. The aim in this paper is to use three heuristic optimization methods, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO), to solve the first-order design (FOD) problem for a small-volume indoor network and make a comparison of their performances. The room is simplified as discretized wall segments and possible viewpoints. Each possible viewpoint is evaluated with a score table representing the wall segments visible from each viewpoint based on scanning geometry constraints. The goal is to find a minimum number of viewpoints that can obtain complete coverage of all wall segments with a minimal sum of incidence angles. The different methods have been implemented and compared in terms of the quality of the solutions, runtime and repeatability. The experiment environment was simulated from a room located on University of Calgary campus where multiple scans are required due to occlusions from interior walls. The results obtained in this research show that PSO and GA provide similar solutions while SA doesn't guarantee an optimal solution within limited iterations. Overall, GA is considered as the best choice for this problem based on its capability of providing an optimal solution and fewer parameters to tune.

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Section: Introductionmentioning

confidence: 99%

A Comparison of Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization in Optimal First-Order Design of Indoor TLS Networks

Jia

Lichti

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…These situations arise mostly in various routing and scheduling problems. Some reported applications are Print press scheduling (Gorenstein 1970 (Wang & Regan, 2002), Planning of autonomous mobile robots (Brumitt et al 2001), Designing satellite surveying systems (Saleh & Chelouah 2004). Therefore, finding a good methodology for the mTSP is important and induces to improve the solution of any other complex routing problems.…”

Section: Literature Surveymentioning

confidence: 99%

Intelligence heuristics to solve a Balanced Routing Problem in Supply Chain

Kannan¹,

Jayanthi²,

Dhanalakshmi³

2017

IJCA

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In today's business system, supply chain competitiveness greatly depends on its capability to handle the challenges of cost reduction, service level improvement and quality enhancement. In this competitive market, customer service level is the most significant factor for the success of the firm. Supply chain network needs to be efficient enough to handle the changing demand patterns. Balanced routing of goods among supply chain entities will improve the asset utilization and customer service level in a supply chain system. Over or under utilization of the supply chain entity will impact the customer service. We develop a decision support system based on three-stage heuristics to solve this balanced routing problem. A case study is illustrated and the DSS is validated for this case study.

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“…When there are multiple receivers or multiple working periods, the problem of finding the best order of sessions for the receivers can be formulated as an mTSP. For technical details refer (Saleh & Chelouah, 2004).…”

Section: Main Applicationsmentioning

confidence: 99%

“…vii. Design of global navigation satellite system surveying networks: A very recent and an interesting application of the mTSP, as investigated by (Saleh & Chelouah, 2004) arises in the design of global navigation satellite system (GNSS) surveying networks. A GNSS is a space-based satellite system which provides coverage for all locations worldwide and is quite crucial in real-life applications such as early warning and management for disasters, environment and agriculture monitoring, etc.…”

Section: Main Applicationsmentioning

confidence: 99%

Traveling Salesman Problem: an Overview of Applications, Formulations, and Solution Approaches

Matai¹,

Singh²,

Mittal³

2010

Traveling Salesman Problem, Theory and Applications

193

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The design of the global navigation satellite system surveying networks using genetic algorithms

Cited by 65 publications

References 9 publications

A Comparison of Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization in Optimal First-Order Design of Indoor TLS Networks

A Comparison of Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization in Optimal First-Order Design of Indoor TLS Networks

Intelligence heuristics to solve a Balanced Routing Problem in Supply Chain

Traveling Salesman Problem: an Overview of Applications, Formulations, and Solution Approaches

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