New Search

Result: 125,568,451

Page of 12,556,846
Articles per Page
by
Show export options
  Select all
Romulo Delarmente Tagalo
Disaster Prevention and Management: An International Journal; doi:10.1108/dpm-07-2020-0225

Abstract:
PurposeThis paper develops a model of social vulnerability. Specifically, it aims to (1) determine the factors of social vulnerability to flood risks and (2) interrogate the discursive structure and framing of vulnerability within the local domain of disaster governance.Design/methodology/approachThis is a descriptive-survey research design mobilized through sequential exploratory mixed method.FindingsFor ordinary people, vulnerability is due to five factors: (1) government inaction, (2) age-based frailty, (3) disability-based social exclusion, (4) weak social capital and (5) material susceptibility. Moreover, there are two patterns of discursive structure surrounding the risk of flooding in Davao del Norte: (1) where Cavendish banana is a favored export commodity of those who are in power, the Pressure-and-Release Model fits within the narrative of land-use changes in the province, and (2) where the local domain of disaster governance frames the DRR as a “hero-villain” normative duality.Practical implicationsAt the policy level, the findings should inform the current government practices in development planning to mitigate flood risks, specifically the proposed Philippine National Land-use Act and the pending Bill to create the Philippine Disaster Risk Reduction and Management (DRRM) Department. Operationally, the “hero-villain” finding challenges the self-awareness of disaster managers and functionaries whose technical trainings inculcated a one-size-fits-all approach to disaster response.Social implicationsThe findings support the theory that disaster and disaster risks are socially constructed realities.Originality/valueThis paper teased out the gap between the people's risks perceptions in Davao del Norte and the government's DRR episteme, and it points to power relations that impede its closing.
R. Ryan Lash, Catherine V. Donovan, Aaron T. Fleischauer, Zack S. Moore, Gibbie Harris, Susan Hayes, Meg Sullivan, April Wilburn, Jonathan Ong, Dana Wright, et al.
MMWR. Morbidity and Mortality Weekly Report, Volume 69, pp 1360-1363; doi:10.15585/mmwr.mm6938e3

Abstract:
This report describes the percentage of investigated persons with COVID-19 who reported contacts and the percentage of contacts who were not reached in two counties in North Carolina.
Masato Dei, Tomoki Fukuba, Sciprofile linkTakayuki Shiina, K. Tokoro
Operations Research Proceedings pp 257-263; doi:10.1007/978-3-030-48439-2_31

Abstract:
Electricity is now traded in various ways in the market. Planning is necessary to buy or sell electricity in the market, because the fluctuations in the market price may incur significant costs. Regardless of the irregularities in power generation due to plant failures or inspections, or inconsistent weather conditions, the electricity demand of the market must be delivered. Therefore, it is necessary to have an operational plan that takes into account the uncertainty of the market price. Such uncertainty problems are usually solved by using the expected value minimization model. However, this model is risk-neutral, and does not consider fluctuations in the costs of different constituents. Accordingly, we propose a conditional value at risk minimization model that avoids the risk of fluctuating costs. In this study, we formulate a stochastic programming model for the operational plan (considering uncertainty), for factories. Further, we show the effectiveness of the proposed model by comparing it with the expected value minimization model.
Sciprofile linkErik Pohl, Christina Scharpenberg, Jutta Geldermann
Operations Research Proceedings pp 141-147; doi:10.1007/978-3-030-48439-2_17

Abstract:
In this paper we present an approach to assess energy and emission reduction measures in container terminals. A modified PROMETHEE V approach is used to select suitable portfolios of these measures based on the decision makers preferences and further inter-dependencies.
Sciprofile linkMarkus Diller, Johannes Lorenz, David Meier
Operations Research Proceedings pp 633-639; doi:10.1007/978-3-030-48439-2_77

Abstract:
This study presents a model in which heterogenous, risk-averse agents can use either (legal) tax optimisation or (illegal) tax evasion to reduce their tax burden and thus increase their utility. In addition to introducing individual variables like risk aversion or income, we allow agents to observe the behaviour of their neighbours. Depending on the behaviour of their peer group’s members, the agents’ utilities may increase or decrease, respectively. Simulation results show that taxpayers favour illegal evasion over legal optimisation in most cases. We find that interactions between taxpayers and their social networks have a deep impact on aggregate behaviour. Parameter changes such as increasing audit rates affect the results, often being intensified by social interactions. The effect of such changes varies depending on whether or not a fraction of agents is considered inherently honest.
Sciprofile linkSusanne Heipcke, Yves Colombani
Operations Research Proceedings pp 677-683; doi:10.1007/978-3-030-48439-2_82

Abstract:
Important current trends influencing the development of modeling environments include expectations on interconnection between optimization and analytics tools, easy and secure deployment in a web-based, distributed setting and not least, the continuously increasing average and peak sizes of data instances and complexity of problems to be solved. After a short discussion of the history of modeling languages and the contributions made by FICO Xpress Mosel to this evolution, we point to a number of implementation variants for the classical travelling salesman problem (TSP) using different MIP-based solution algorithms as an example of employing Mosel in the context of parallel or distributed computing, for interacting with a MIP solver, and for the graphical visualisation of results. We then highlight some newly introduced features and improvements to the Mosel language that are of particular interest for the development of large-scale optimization applications.
Operations Research Proceedings pp 707-714; doi:10.1007/978-3-030-48439-2_86

Abstract:
Over the past years, closed-loop supply chains (CLSC) gained a considerable attention in both academia and industry due to environmental regulations and concerns about sustainability. Although various problems in CLSC’s are addressed by researchers, not much attention is given to the effects of closing the loop in supply chains. In this study, we propose a set of linear programming models for both forward and closed-loop supply chains to see the economic and environmental effects of closing the loop. In addition to the case where there is no emission regulation, we also study the carbon cap policy and compare the forward and closed-loop supply chains under this policy. Computational results bring two important insights to us. First, we see that there are instances in which closing the loop may bring significant cost and emission reductions. Second, we observe that it may be possible to work under lower carbon caps by closing the loop in supply chains.
Sciprofile linkKathrin Maassen, Paz Perez-Gonzalez
Operations Research Proceedings pp 555-561; doi:10.1007/978-3-030-48439-2_67

Abstract:
In static-deterministic flow shop scheduling, solution algorithms are often tested by problem instances with uniformly distributed processing times. However, there are scheduling problems where a certain structure, variability or distribution of processing times appear. While the influence of these aspects on common objectives, like makespan and total completion time, has been discussed intensively, the efficiency-oriented objectives core idle time and core waiting time have not been taken into account so far. Therefore, a first computational study using complete enumeration is provided to analyze the influence of different structures of processing times on core idle time and core waiting time. The results show that in some cases an increased variability of processing times can lead to easier solvable problems.
Sciprofile linkKaitlin Benedict, Noelle Angelique M. Molinari, Brendan R. Jackson
MMWR. Morbidity and Mortality Weekly Report, Volume 69, pp 1343-1346; doi:10.15585/mmwr.mm6938a2

Abstract:
This report describes how public awareness of fungal diseases can prevent incorrect treatment and improve outcomes.
Operations Research Proceedings pp 651-657; doi:10.1007/978-3-030-48439-2_79

Abstract:
Causal Loop Diagrams (CLDs) are a flexible and valuable tool for diagramming the feedback structure of systems. In strategic decision-making and management, we use CLDs to structure and explore complex decision-making situations, to foster learning, as a basis for simulation models, and to communicate simulation results. However, the crucial dissemination of CLDs and the possible learnings beyond the project-team is challenging. To overcome this problem, we developed a Domain-Specific Language that allows modeling experts with little programming experience to generate visual representations of CLDs that (1) replace the most complicated CLD elements with a step-by-step explanation and (2) strive to lower the barriers to learning while addressing a broader target audience.
Page of 12,556,846
Articles per Page
by
Show export options
  Select all
Back to Top Top