scholarly journals EFFECTIVENESS OF CENTRALIZED MECHANISM OF LABOR RESOURCE ALLOCATION – EXPERIMENTAL TESTS

2017 ◽  
Vol 16 (4) ◽  
pp. 133-140
Author(s):  
Łukasz Pietrych
Keyword(s):  
Resource Allocation ◽  
Labor Market ◽  
Experimental Tests ◽  
Resources Allocation ◽  
Allocation System ◽  
Matching Efficiency ◽  
Matching Mechanism ◽  
Labor Resources ◽  
Stable Allocations ◽  
Resource Allocation System

In the article the issue of labor resources allocation in the context of the emerging field of economic sciences known as “market design” was discussed. The assumptions for the designed experimental environment were discussed. An experimental variable and variables dependent on it were defined. The main objective of the paper is to develop a matching mechanism for participants in the experiment as a basis for a broader, centralized resource allocation system in the labor market. The study confirmed the hypothesis that fulfilling the assumptions of stable allocations theory improves the matching efficiency in the labor market and thus reduces the frictional unemployment.

Ready for take‐off: realising the potential of the education and training consortia

1998 ◽  
Vol 24 (5) ◽  
pp. 188-191 ◽  
Author(s):  
John Edmonstone
Keyword(s):  
Resource Allocation ◽  
Good Practice ◽  
Workforce Planning ◽  
Education And Training ◽  
Planning System ◽  
Top Down ◽  
Allocation System ◽  
Developing System ◽  
Resource Allocation System ◽  
And Training

Education consortia are now over 18 months old and can be seen as a “hybrid” between a top‐down resource allocation system and a bottom‐up workforce planning system. The strengths and weaknesses of the developing system are identified, as is emerging good practice in consortia operations. A model for consortia working which emphasises strategic working is proposed.

Apache Airavata Resource Allocation System

2018 ◽  
Author(s):  
Harsha Phulwani ◽  
Madrina Thapa ◽  
Suresh Marru ◽  
Marlon Pierce ◽  
Sudhakar Pamidighantam ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Allocation System ◽  
Resource Allocation System

PortSec: Port Security Risk Management and Resource Allocation System

2009 ◽  
Vol 42 (15) ◽  
pp. 135-142 ◽  
Author(s):  
Michael D. Orosz ◽  
Carl Southwell ◽  
Anthony Barrett ◽  
Onur Bakir ◽  
Jennifer Chen ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Risk Management ◽  
Security Risk ◽  
Port Security ◽  
Allocation System ◽  
Security Risk Management ◽  
Resource Allocation System

A RFID-based Resource Allocation System for garment manufacturing

2013 ◽  
Vol 40 (2) ◽  
pp. 784-799 ◽  
Author(s):  
C.K.H. Lee ◽  
K.L. Choy ◽  
G.T.S. Ho ◽  
K.M.Y. Law
Keyword(s):  
Resource Allocation ◽  
Allocation System ◽  
Garment Manufacturing ◽  
Resource Allocation System

scholarly journals Enhancement in resource allocation system for cloud environment using modified grey wolf technique

2020 ◽  
Vol 20 (3) ◽  
pp. 1530
Author(s):  
Soukaina Ouhame ◽  
Youssef Hadi
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Fitness Function ◽  
Advanced Technology ◽  
Grey Wolf ◽  
Cloud Environment ◽  
Abc Algorithm ◽  
Allocation System ◽  
A New Technique ◽  
Resource Allocation System

<p class="normal">Cloud computing is an advanced technology which provides services with the help of internet. These services work under the rule of pay and gain. The services consist of hardware and software used in different fields of life. Due to growth of cloud computing the number of users are increased and their demand for better services also  increased with the passage of time. Cloud computing faces different issues. One of them is resource scheduling. In this paper a new technique is used for improvement of scheduling in cloud computing. The improvement took place in GWO algorithm. Two main sections of this algorithm are modified, which are local search section and fitness function value. The above proposed technique is used to improve three main parameters of scheduling that are energy consumption, throughput and average network executation time in VM for cloud computing. The  techniques results are compared with ABC algorithm and GWO algorithm. The results show that proposed algorithm improves in the three main parameters  of scheduling for cloud computing.</p>

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