Least impact algorithm for resource allocation

1993 ◽  
Vol 20 (2) ◽  
pp. 180-188 ◽  
Author(s):  
Osama Moselhi ◽  
Pasit Lorterapong
Keyword(s):  
Resource Allocation ◽  
Present Model ◽  
Resource Constraints ◽  
Negative Impact ◽  
Scheduling Algorithm ◽  
Impact Model ◽  
Planning And Scheduling ◽  
Resource Conflict ◽  
Heuristic Scheduling ◽  
Scheduling Heuristic

A new heuristic-based resource-scheduling algorithm called the least impact model is developed. Unlike available heuristic models, the least impact model allocates resources to a set or a group of activities simultaneously rather than sequentially to individual activities, so as to minimize the negative impact on the remaining total float calculated from a project CPM-type network. A new parameter called future float is introduced as an indicator for assigning scheduling priorities to the sets of activities being considered. Activity sets are generated by first considering all possible combinations of current activities experiencing resource conflict and then narrowing them down to those feasible, which in turn are assigned priorities for allocation of resources based on the least negative impact on the duration of the project. Two examples are worked out to illustrate the use and capabilities of the present model. The results indicate that the least impact model is capable of producing better solutions than those generated from the commonly used total float and the recently proposed current float techniques. Key words: planning and scheduling, resource allocation, resource-constraints scheduling, heuristic scheduling.

Placement of Digital Microfluidic Biochips via a New Evolutionary Algorithm

2021 ◽  
Vol 26 (6) ◽  
pp. 1-22
Author(s):  
Chen Jiang ◽  
Bo Yuan ◽  
Tsung-Yi Ho ◽  
Xin Yao
Keyword(s):  
Evolutionary Algorithm ◽  
Resource Constraints ◽  
Scheduling Algorithm ◽  
Search Space ◽  
Placement Problem ◽  
Heuristic Scheduling ◽  
Microfluidic Biochips ◽  
Feasible Solutions ◽  
Digital Microfluidic ◽  
Operation Scheduling

Digital microfluidic biochips (DMFBs) have been a revolutionary platform for automating and miniaturizing laboratory procedures with the advantages of flexibility and reconfigurability. The placement problem is one of the most challenging issues in the design automation of DMFBs. It contains three interacting NP-hard sub-problems: resource binding, operation scheduling, and module placement. Besides, during the optimization of placement, complex constraints must be satisfied to guarantee feasible solutions, such as precedence constraints, storage constraints, and resource constraints. In this article, a new placement method for DMFB is proposed based on an evolutionary algorithm with novel heuristic-based decoding strategies for both operation scheduling and module placement. Specifically, instead of using the previous list scheduler and path scheduler for decoding operation scheduling chromosomes, we introduce a new heuristic scheduling algorithm (called order scheduler) with fewer limitations on the search space for operation scheduling solutions. Besides, a new 3D placer that combines both scheduling and placement is proposed where the usage of the microfluidic array over time in the chip is recorded flexibly, which is able to represent more feasible solutions for module placement. Compared with the state-of-the-art placement methods (T-tree and 3D-DDM), the experimental results demonstrate the superiority of the proposed method based on several real-world bioassay benchmarks. The proposed method can find the optimal results with the minimum assay completion time for all test cases.

Research on Resource Allocation Strategy of PaaS Platform

2019 ◽  
Vol 12 (1) ◽  
pp. 63-76
Author(s):  
Hongen Peng ◽  
Yabin Xu
Keyword(s):  
Resource Allocation ◽  
Waiting Time ◽  
Ant Colony Algorithm ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Optimal Solution ◽  
Allocation Model ◽  
Heuristic Scheduling ◽  
Local Optimal Solution ◽  
Resource Allocation Strategy

In order to allocate elastic resource to the application of PaaS platform, the authors analyze the key technologies and the particularity of resource scheduling in PaaS platform, and design an application-oriented resource allocation model and heuristic scheduling algorithm based on an ant colony algorithm. Different from the existing resource allocation methods based on virtual machines in IaaS, the scheduling strategy is based on Application in PaaS platform. According to the analysis of the application layout, the heuristic algorithm is used to minimize the number of application migration and reduce the waiting time of the task. In order to avoid falling into the loop or local optimal solution, the authors also used a tabu search technique. The results of comparative experiments show that, this strategy has higher resource utilization and shorter task waiting time.

Task Scheduling in Multi-Process with Resource Constraints under MG Workflow

2008 ◽  
Vol 33-37 ◽  
pp. 1425-1430
Author(s):  
Feng Xiong ◽  
Yi Ping Yuan ◽  
Yu Ying Wang ◽  
Guang Wen Wang
Keyword(s):  
Task Scheduling ◽  
Resource Constraints ◽  
Critical Path ◽  
Scheduling Algorithm ◽  
Limited Resource ◽  
Workflow Engine ◽  
Priority Rules ◽  
Heuristic Scheduling ◽  
Time Parameters ◽  
Set Up

In manufacturing Grid workflow, multiple tasks share a common and limited resource pool. In order to solve task scheduling in multi-process with resource constraints under MG workflow, the Task-Resource Constrained model is set up to descript the assignment relation between task and resource. The framework of the task scheduling and the scheduling policies are also presented that can readjust the tasks according to the priority rules and the time parameters in the process. Then we present a heuristic scheduling algorithm that includes multiple policies. The heuristic scheduling algorithm will update the critical path of DAG (Direct Acyclic Graph) and the beginning time of post-tasks. MG Workflow engine can dynamically schedule the resources according the task requirement. An example is given to illustrate the method at last.

ANALYSIS OF MEASURES TO REDUCE ECOLOGICAL AND ECONOMIC DAMAGE FROM AUTOMOBILE TRANSPORT

2020 ◽  
Author(s):  
V.N. Kurdyukov ◽  
◽  
T.V. Lebedeva ◽  
Keyword(s):  
Resource Allocation ◽  
Negative Impact ◽  
The State ◽  
Point Of View ◽  
Motor Vehicles ◽  
Economic Damage ◽  
Agriculture Education

The article considers common classifications of measures to reduce environmentaleconomic damage from motor vehicles. Classification from the point of view of control impact is proposed, which allows to take into account relations between the state and citizens in the field of reduction of negative impact of motor vehicles on the environment. The analysis of the classification made it possible to identify areas of activity for improving the efficiency of management impacts, taking into account the incentives of citizens to comply with the requirements of the legislation and to create conditions for their exceeding. Increasing the efficiency of resource allocation in the Territory will allow the released funds to be allocated to the development of industry, agriculture, education and science.

scholarly journals Let’s Focus on Solutions to Entrepreneurial Ill-Being! Recovery Interventions to Enhance Entrepreneurial Well-Being

2021 ◽  
pp. 104225872110064
Author(s):  
Amanda Jasmine Williamson ◽  
J. Jeffrey Gish ◽  
Ute Stephan
Keyword(s):  
Resource Constraints ◽  
Negative Impact ◽  
Well Being ◽  
Natural Recovery ◽  
Health And Well Being ◽  
Scholarly Inquiry

Entrepreneurship is uniquely stressful. Entrepreneurs often cannot avoid entrepreneurial stressors (e.g., uncertainty, workload, resource constraints) and these stressors can deter natural recovery activities (e.g., detachment and sleep). Yet, entrepreneurs may be able to lessen the negative impact of stress on their well-being, health, and productivity by engaging in recovery. In this editorial, we outline how scholars can employ recovery interventions to ameliorate some of entrepreneurship’s ill effects and support entrepreneurs’ health, well-being, and productivity. We aim to move the focus of scholarly inquiry from documenting the health and well-being challenges of entrepreneurs, toward identifying and implementing solutions to support entrepreneurs.

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