scholarly journals Optimization of surface utilization using heuristic approaches

2007 ◽  
Author(s):  
Y. Langer ◽  
M. Bay ◽  
Y. Crama ◽  
F. Bair ◽  
J. D. Caprace ◽  
...  
Keyword(s):  
Heuristic Approaches

Division of labor

2018 ◽  
Author(s):  
Phanish Puranam
Keyword(s):  
Division Of Labor ◽  
Task Allocation ◽  
Task Structure ◽  
Heuristic Approaches ◽  
Object Based ◽  
The Creation ◽  
Task Division ◽  
And Task

Division of labor involves task division and task allocation. An extremely important consequence of task division and allocation is the creation of interdependence between agents. In fact, division of labor can be seen as a process that converts interdependence between tasks into interdependence between agents. While there are many ways in which the task structure can be chunked and divided among agents, two important heuristic approaches involve division of labor by activity vs. object. I show that a choice between these two forms of division of labor only arises when the task structure is non-decomposable, but the product itself is decomposable. When the choice arises, a key criterion for selection between activity vs. object-based division of labor is the gain from specialization relative to the gain from customization.

Exact and heuristic approaches to reschedule helicopter flights for personnel transportation in the oil industry

2021 ◽  
Vol 151 ◽  
pp. 102322
Author(s):  
Thiago Vieira ◽  
Jonathan De La Vega ◽  
Roberto Tavares ◽  
Pedro Munari ◽  
Reinaldo Morabito ◽  
...  
Keyword(s):  
Oil Industry ◽  
Heuristic Approaches

GEOMETRIC ALGORITHMS FOR THE CONSTRAINED 1-D K-MEANS CLUSTERING PROBLEMS AND IMRT APPLICATIONS

2009 ◽  
Vol 20 (02) ◽  
pp. 361-377
Author(s):  
DANNY Z. CHEN ◽  
MARK A. HEALY ◽  
CHAO WANG ◽  
BIN XU
Keyword(s):  
Radiation Therapy ◽  
Treatment Planning ◽  
Intensity Modulated Radiation Therapy ◽  
Geometric Algorithms ◽  
Maximum Difference ◽  
Continuous Version ◽  
Heuristic Approaches ◽  
Clustering Problem ◽  
Intensity Modulated ◽  
Clustering Problems

In this paper, we present efficient geometric algorithms for the discrete constrained 1-D K-means clustering problem and extend our solutions to the continuous version of the problem. One key clustering constraint we consider is that the maximum difference in each cluster cannot be larger than a given threshold. These constrained 1-D K-means clustering problems appear in various applications, especially in intensity-modulated radiation therapy (IMRT). Our algorithms improve the efficiency and accuracy of the heuristic approaches used in clinical IMRT treatment planning.

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