A Parallel Scenario Processing Algorithm in Environmental Decision Support Systems

2014 ◽  
Vol 962-965 ◽  
pp. 2735-2740
Author(s):  
Jian Hui Zhao ◽  
Ming Yu Wang ◽  
Zhi Yu Li ◽  
Ji Ke Chang ◽  
Qian Qian Hu
Keyword(s):  
Decision Support ◽  
Scenario Analysis ◽  
Message Passing ◽  
Message Passing Interface ◽  
Planning Problem ◽  
Analysis Method ◽  
Energy And Environment ◽  
Restoration Planning ◽  
Environmental Decision Making ◽  
Environmental Decision

The scenario analysis method is used widespread in environmental management fields. Massive scenarios used in the applications lead to huge computing workloads and time-consuming. A parallel computing algorithm based on the Message Passing Interface (MPI) standard was proposed to enhance the computing performance of scenario generating and calculating. By taking a river restoration planning problem as a case study, the proposed algorithm was applied in a decision support system and tested on a multi-core workstation. Experimental results show that when performed on a quad-core workstation, the algorithm reduced the execution time to a quarter of the former, with a stable speedup factor of 3.8 at different amounts of scenarios. It is indicated that the proposed algorithm is practical in environmental decision-making procedure, with special reference to the general scenario analysis method and other similar applications in the fields of energy and environment.

Risk today, certainty tomorrow: The influence of construal level on environmental decision-making

2011 ◽  
Author(s):  
Allison Sweeney ◽  
Amanda Hamilton ◽  
Ashley Beck ◽  
Brian Detweiler-Bedell ◽  
Jerusha Detweiler-Bedell
Keyword(s):  
Decision Making ◽  
Construal Level ◽  
Environmental Decision Making ◽  
Environmental Decision

Multi-level Parallelization of Genotype Imputation on Supercomputers

2020 ◽  
Vol 15 ◽  
Author(s):  
Weiwen Zhang ◽  
Long Wang ◽  
Theint Theint Aye ◽  
Juniarto Samsudin ◽  
Yongqing Zhu
Keyword(s):  
Association Study ◽  
Message Passing ◽  
High Performance ◽  
Message Passing Interface ◽  
Genome Wide Association Study ◽  
Job Scheduling ◽  
Genotype Imputation ◽  
Job Level ◽  
Multi Level ◽  
High Performance Requirement

Background: Genotype imputation as a service is developed to enable researchers to estimate genotypes on haplotyped data without performing whole genome sequencing. However, genotype imputation is computation intensive and thus it remains a challenge to satisfy the high performance requirement of genome wide association study (GWAS). Objective: In this paper, we propose a high performance computing solution for genotype imputation on supercomputers to enhance its execution performance. Method: We design and implement a multi-level parallelization that includes job level, process level and thread level parallelization, enabled by job scheduling management, message passing interface (MPI) and OpenMP, respectively. It involves job distribution, chunk partition and execution, parallelized iteration for imputation and data concatenation. Due to the design of multi-level parallelization, we can exploit the multi-machine/multi-core architecture to improve the performance of genotype imputation. Results: Experiment results show that our proposed method can outperform the Hadoop-based implementation of genotype imputation. Moreover, we conduct the experiments on supercomputers to evaluate the performance of the proposed method. The evaluation shows that it can significantly shorten the execution time, thus improving the performance for genotype imputation. Conclusion: The proposed multi-level parallelization, when deployed as an imputation as a service, will facilitate bioinformatics researchers in Singapore to conduct genotype imputation and enhance the association study.

Evaluating alternative environmental decision support matrices for future Higg MSI scenarios

2021 ◽  
Author(s):  
Valentina Prado ◽  
Jesse Daystar ◽  
Michele Wallace ◽  
Steven Pires ◽  
Lise Laurin
Keyword(s):  
Decision Support ◽  
Environmental Decision

scholarly journals Decision support framework for the regional facility location and development planning problem

2021 ◽  
Author(s):  
David Kik ◽  
Matthias Gerhard Wichmann ◽  
Thomas Stefan Spengler
Keyword(s):  
Decision Support ◽  
Facility Location ◽  
Future Orientation ◽  
Real Life ◽  
Development Planning ◽  
Major Influence ◽  
Location Decisions ◽  
Planning Problem ◽  
Location Factor ◽  
Decision Support Framework

AbstractLocation choice is a crucial planning task with major influence on a company’s future orientation and competitiveness. It is quite complex, since multiple location factors are usually of decision-relevance, incomparable, and sometimes conflictual. Further, ongoing urbanization is associated with locational dynamics posing major challenges for the regional location management of companies and municipalities. For example, respecting urban space as location factor, a scarcity growing over time leads to different assessment and requirements on a company’s behalf. For both companies and municipalities, there is a need for location development which implies an active change of location factor characteristics. Accordingly, considering locational dynamics is vital, as they may be decisive in the location decision-making. Although certain dynamics are considered within conventional Facility Location Problem (FLP) approaches, a systematic consideration of active location development is missing so far. Consequently, they may propagate long-term unfavorable location decisions, as major potentials associated with company-driven and municipal development measures are neglected. Therefore, this paper introduces a comprehensive decision support framework for the Regional Facility Location and Development planning Problem (RFLDP). It provides an operationalization of development measures, and thus anticipates dynamic adaptations to the environment. An established multi-criteria approach is extended to this new application. A complementary guideline ensures its meaningful applicability by practitioners. Based on a real-life case study, the decision support framework’s strength for practical application is demonstrated. Here, major advantages over conventional FLP approaches are highlighted. It is shown that the proposed methodology results in alternative location decisions which are structurally superior.

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