Routing through open spaces – A performance comparison of algorithms

Hahmann, Stefan; Miksch, Jakob; Resch, Bernd; Lauer, Johannes; Zipf, Alexander

doi:10.1080/10095020.2017.1399675

Cited by 25 publications

(25 citation statements)

References 17 publications

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“…Furthermore, it is widely accepted in the literature [83,84] that these open spaces provide visual access to the building which facilitates the legibility of the building [85] and orientation [86]. In contrast, this freedom of movement induces difficulties in modeling open spaces and modeling the routing in these spaces, which have been outlined and examined in a number of studies (e.g., [87,88]).…”

Section: Indoor Navigation Situationsmentioning

confidence: 99%

On the Right Track: Comfort and Confusion in Indoor Environments

Vanhaeren

Cock

Lapon

et al. 2020

IJGI

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Indoor navigation systems are not well adapted to the needs of their users. The route planning algorithms implemented in these systems are usually limited to shortest path calculations or derivatives, minimalizing Euclidian distance. Guiding people along routes that adhere better to their cognitive processes could ease wayfinding in indoor environments. This paper examines comfort and confusion perception during wayfinding by applying a mixed-method approach. The aforementioned method combined an exploratory focus group and a video-based online survey. From the discussions in the focus group, it could be concluded that indoor wayfinding must be considered at different levels: the local level and the global level. In the online survey, the focus was limited to the local level, i.e., local environmental characteristics. In this online study, the comfort and confusion ratings of multiple indoor navigation situations were analyzed. In general, the results indicate that open spaces and stairs need to be taken into account in the development of a more cognitively-sounding route planning algorithm. Implementing the results in a route planning algorithm could be a valuable improvement of indoor navigation support.

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Section: Indoor Navigation Situationsmentioning

confidence: 99%

On the Right Track: Comfort and Confusion in Indoor Environments

Vanhaeren

Cock

Lapon

et al. 2020

IJGI

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“…For future studies, the following items are suggested based on the main limitations of the research. Heuristic and metaheuristic methods may be implemented to solve the problem in large scales efficiently, eg, as proposed by Song and Cheng, Hahmann et al, Babaee Tirkolaee et al, Goli et al, Tirkolaee et al, and Sangaiah et al Other uncertainty techniques such as fuzzy theory, grey systems, and stochastic optimal control could be compared to the current robust optimization approach for evaluating different policies under various well‐known techniques. Moreover, to make the model closer to the real‐world conditions, other objective functions including distribution reliability maximization or customers' satisfaction maximization can be studied as well.…”

Section: Conclusion and Future Research Directionsmentioning

confidence: 99%

A robust green traffic‐based routing problem for perishable products distribution

Tirkolaee

Hadian

Weber

et al. 2019

Computational Intelligence

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Nowadays, transportation and logistics are considered as the drivers of economic development in the countries due to their impacts on the main variables of the country's economy such as production, employment, price, and the cost of living. Statistics indicate that fuel consumption constructs a major part of transportation costs, where its optimization leads to the creation of an energy‐efficient and sustainable transportation system. On the other hand, vehicles' traffic is also one of the main criteria affecting the travel time of vehicles between demand nodes in a supply chain, increasing fuel consumption, and, consequently, damaging effects of greenhouse gasses. In this paper, a novel robust mixed‐integer linear programming model is developed for a green vehicle routing problem with intermediate depots considering different urban traffic conditions, fuel consumption, time windows of services, and uncertain demand for perishable products. To validate and solve the suggested model, CPLEX solver of GAMS software is employed as an exact method. Finally, a case study problem is investigated to evaluate the applicability of the proposed model and determine the optimal managerial insights and policies in the real‐world conditions using sensitivity analyses. Moreover, a novel robustness threshold comparison is conducted to find the optimal level of budget assignment.

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“…The simplification of optimization concept and strategies to further inventions establishes an active area of research in the field of mathematics, science, and engineering. The term optimization also referred as mathematics‐based encoding, which is the gathering of mathematical procedures and techniques used for resolving numerical complications across diversified regions, comprising financial and business activities such as inventory control modeling, and generating of shortest route by comparing various open space procedures with respect to diverse optimization constraints and also widespread use in the timber operational industry to achieve finest cutting standards within specific bounds of machining factors . The current developments in computational advancement move away from the conventional strategies to contemporary nature inspired metaheuristic strategies.…”

Section: Introductionmentioning

confidence: 99%

Improved spotted hyena optimizer with space transformational search for training pi‐sigma higher order neural network

Panda

Majhi

2020

Computational Intelligence

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Spotted hyena optimizer (SHO) is a recently developed swarm‐based algorithm in the field of metaheuristic research, for solving realistic engineering design constraint and unconstrained difficulties. To resolve complicated nonlinear physical world tasks, at times, SHO reveals deprived performance concerning to explorative strength. So, to enhance the explorative strength along with exploitation in the search region, an attempt has been made by proposing the enhanced version of classical SHO. The suggested method is designated as space transformation search (STS)‐SHO. In STS‐SHO, a new evolutionary technique named as STS technique has been incorporated with original SHO. The suggested method has been assessed by IEEE CEC 2017 benchmark problems. The efficacy of the said method has been proven by using standard measures such as given performance metrics in CEC 2017, complexity analysis, convergence analysis, and statistical implications. Further as real‐world application, the said algorithm has been applied to train pi‐sigma neural network by means of 13 benchmark datasets considered from UCI depository. From the article it can be concluded that the suggested method STS‐SHO is an effective and trustworthy algorithm, which has the ability to resolve real‐life optimization complications.

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Routing through open spaces – A performance comparison of algorithms

Cited by 25 publications

References 17 publications

On the Right Track: Comfort and Confusion in Indoor Environments

On the Right Track: Comfort and Confusion in Indoor Environments

A robust green traffic‐based routing problem for perishable products distribution

Improved spotted hyena optimizer with space transformational search for training pi‐sigma higher order neural network

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