A Holonic Approach to Myopic Behavior Correction for the Allocation Process in Flexible-Job Shops Using Recursiveness

2012 ◽  
pp. 115-128 ◽  
Author(s):  
Gabriel Zambrano Rey ◽  
Nassima Aissani ◽  
Abdelghani Bekrar ◽  
Damien Trentesaux
Keyword(s):  
Job Shops ◽  
Allocation Process

The Right to Housing: Challenges Associated with the ‘Waiting List System’ Ekurhuleni Metropolitan Municipality V Various Occupiers, Eden Park Extension 5 2014 3 SA 23 (SCA)

2017 ◽  
Vol 30 (1) ◽  
pp. 112-121
Author(s):  
Shamier Ebrahim
Keyword(s):  
Supreme Court ◽  
Waiting Lists ◽  
The State ◽  
Waiting List ◽  
Allocation Process ◽  
The Supreme Court ◽  
The Right ◽  
The Impact ◽  
Court Of Appeal

The right to adequate housing is a constitutional imperative which is contained in section 26 of the Constitution. The state is tasked with the progressive realisation of this right. The allocation of housing has been plagued with challenges which impact negatively on the allocation process. This note analyses Ekurhuleni Metropolitan Municipality v Various Occupiers, Eden Park Extension 51 which dealt with a situation where one of the main reasons provided by the Supreme Court of Appeal for refusing the eviction order was because the appellants subjected the unlawful occupiers to defective waiting lists and failed to engage with the community regarding the compilation of the lists and the criteria used to identify beneficiaries. This case brings to the fore the importance of a coherent (reasonable) waiting list in eviction proceedings. This note further analyses the impact of the waiting list system in eviction proceedings and makes recommendations regarding what would constitute a coherent (reasonable) waiting list for the purpose of section 26(2) of the Constitution.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

2020 ◽  
Vol 10 (5) ◽  
pp. 1557
Author(s):  
Weijia Feng ◽  
Xiaohui Li
Keyword(s):  
Resource Allocation ◽  
Incomplete Information ◽  
Stackelberg Game ◽  
Superior Performance ◽  
Channel Gain ◽  
Mobile Users ◽  
Pricing Strategies ◽  
Game Equilibrium ◽  
Allocation Process ◽  
Realistic Situation

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.

scholarly journals The best task allocation process is to decide on one’s own: effects of the allocation agent in human–robot interaction on perceived work characteristics and satisfaction

2020 ◽  
Author(s):  
Alina Tausch ◽  
Annette Kluge
Keyword(s):  
Task Allocation ◽  
New Technologies ◽  
Human Robot Interaction ◽  
Work Characteristics ◽  
Allocation Decision ◽  
Robot Interaction ◽  
Work Systems ◽  
Organizational Unit ◽  
Allocation Process ◽  
Task Identity

AbstractNew technologies are ever evolving and have the power to change human work for the better or the worse depending on the implementation. For human–robot interaction (HRI), it is decisive how humans and robots will share tasks and who will be in charge for decisions on task allocation. The aim of this online experiment was to examine the influence of different decision agents on the perception of a task allocation process in HRI. We assume that inclusion of the worker in the allocation will create more perceived work resources and will lead to more satisfaction with the allocation and the work results than a decision made by another agent. To test these hypotheses, we used a fictional production scenario where tasks were allocated to the participant and a robot. The allocation decision was either made by the robot, by an organizational unit, or by the participants themselves. We then looked for differences between those conditions. Our sample consisted of 151 people. In multiple ANOVAs, we could show that satisfaction with the allocation process, the solution, and with the result of the work process was higher in the condition where participants themselves were given agency in the allocation process compared to the other two. Those participants also experienced more task identity and autonomy. This has implications for the design of allocation processes: The inclusion of workers in task allocation can play a crucial role in leveraging the acceptance of HRI and in designing humane work systems in Industry 4.0.

scholarly journals Queue Length Forecasting in Complex Manufacturing Job Shops

Forecasting ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 322-338
Author(s):  
Marvin Carl May ◽  
Alexander Albers ◽  
Marc David Fischer ◽  
Florian Mayerhofer ◽  
Louis Schäfer ◽  
...  
Keyword(s):  
Operations Management ◽  
Queue Length ◽  
Manufacturing Systems ◽  
Production Control ◽  
Data Sets ◽  
Job Shops ◽  
Static Data ◽  
Queue Lengths ◽  
Operational Excellence

Currently, manufacturing is characterized by increasing complexity both on the technical and organizational levels. Thus, more complex and intelligent production control methods are developed in order to remain competitive and achieve operational excellence. Operations management described early on the influence among target metrics, such as queuing times, queue length, and production speed. However, accurate predictions of queue lengths have long been overlooked as a means to better understanding manufacturing systems. In order to provide queue length forecasts, this paper introduced a methodology to identify queue lengths in retrospect based on transitional data, as well as a comparison of easy-to-deploy machine learning-based queue forecasting models. Forecasting, based on static data sets, as well as time series models can be shown to be successfully applied in an exemplary semiconductor case study. The main findings concluded that accurate queue length prediction, even with minimal available data, is feasible by applying a variety of techniques, which can enable further research and predictions.

Scheduling for on-time completion in job shops using feasibility function

2003 ◽  
Vol 45 (1) ◽  
pp. 215-229 ◽  
Author(s):  
Attila Lengyel ◽  
Itsuo Hatono ◽  
Kanji Ueda
Keyword(s):  
Job Shops
Sign in / Sign up

Export Citation Format

Share Document