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Dynamic minimum set problem for reserve design: Heuristic solutions for large problems.

ABSTRACT: Conversion of wild habitats to human dominated landscape is a major cause of biodiversity loss. An approach to mitigate the impact of habitat loss consists of designating reserves where habitat is preserved and managed. Determining the most valuable areas to preserve in a landscape is called the reserve design problem. There exists several possible formulations of the reserve design problem, depending on the objectives and the constraints. In this article, we considered the dynamic problem of designing a reserve that contains a desired area of several key habitats. The dynamic case implies that the reserve cannot be designed in one time step, due to budget constraints, and that habitats can be lost before they are reserved, due for example to climate change or human development. We proposed two heuristics strategies that can be used to select sites to reserve each year for large reserve design problem. The first heuristic is a combination of the Marxan and site-ordering algorithms and the second heuristic is an augmented version of the common naive myopic heuristic. We evaluated the strategies on several simulated examples and showed that the augmented greedy heuristic is particularly interesting when some of the habitats to protect are particularly threatened and/or the compactness of the network is accounted for.

SUBMITTER: Bonneau M

PROVIDER: S-EPMC5854297 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Dynamic minimum set problem for reserve design: Heuristic solutions for large problems.

Bonneau Mathieu M Sabbadin Régis R Johnson Fred A FA Stith Bradley B

PloS one 20180315 3

Conversion of wild habitats to human dominated landscape is a major cause of biodiversity loss. An approach to mitigate the impact of habitat loss consists of designating reserves where habitat is preserved and managed. Determining the most valuable areas to preserve in a landscape is called the reserve design problem. There exists several possible formulations of the reserve design problem, depending on the objectives and the constraints. In this article, we considered the dynamic problem of de ...[more]

PMID: 29543830

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Project description:The present data was applied to investigate the relationship between students' attitude towards, and performance in mathematics word problems (MWTs), mediated by the active learning heuristic problem-solving (ALHPS) approach. Specifically, the data reports on the correlation between students' performance and their attitude towards linear programming (LP) word tasks (ATLPWTs). Four types of data were collected from 608 grade 11 students who were selected from eight secondary schools (both public and private). The participants were from two districts: Mukono and Mbale in Central Uganda and Eastern Uganda respectively. A mixed methods approach with a quasi-experimental non-equivalent group design was adopted. The data collection tools included standardized LP achievement tests (LPATs) for pre-test and post-test, the attitude towards mathematics inventory-short form (ATMI-SF), a standardized active learning heuristic problem-solving tool, and an observation scale. The data were collected from October 2020 to February 2021. All the four tools were validated by mathematics experts, pilot-tested, and found reliable and suitable for measuring students' performance and attitude towards LP word tasks. To achieve the purpose of the study, eight intact classes from the sampled schools were selected using the cluster random sampling method. Of these, and by a toss of a coin, four were randomly assigned to the comparison group while the other four were randomly assigned to the treatment group. All teachers from the treatment group were trained on the application of the ALHPS approach before intervention. The participants' demographic data (identification numbers, age, gender, school status, and school location) were presented together with the pre-test and the post-test raw scores obtained before and after intervention respectively. The LPMWPs test items were administered to the students to explore and assess their problem-solving (PS), graphing (G), and Newman error analysis strategies. Students' percentage scores in the pre-test and post-test were based on mathematizing word problems to optimization of LP problems. Data were analyzed in line with the purpose of the study, and the stated objectives. This data supplements other data sets and empirical findings on the mathematization of mathematics word problems, problem-solving strategies, graphing and error analysis prompts. This data may serve and provide some insights into the extent to which ALHPS strategies support students' conceptual understanding, procedural fluency, and reasoning among learners in secondary schools and beyond. The LPMWPs test items in the supplementary data files can also act as a basis for the application of mathematics in real-life scenarios beyond the compulsory level. The data is intended to develop, support, and strengthen students' problem-solving and critical thinking skills with the main goal of enhancing instruction and assessment in secondary schools and beyond.

Project description:Current trends in the United States health care landscape call for innovative and adaptive approaches to improve outcomes and reduce inefficiencies. Design Thinking is an innovative approach to problem-solving that leverages insights from the end-users of new products, services, and experiences in order to develop best-fit solutions that are rapidly prototyped and iteratively refined. When compared to traditional problem-solving methods in health care and other public health adjacent fields, Design Thinking leads to more successful and sustainable interventions. Design Thinking has facilitated improvements in patient, provider, and community satisfaction, and in public health, has increased efficiency and collaboration in intervention development. Given the promising nature of Design Thinking as an effective problem-solving method, it follows that Design Thinking training would prove a beneficial addition to public health education. The integration of Design Thinking in public health education may equip public health leaders with essential skills necessary to understand and more effectively approach historically intractable challenges. This article describes the development and evaluation of a hands-on Design Thinking workshop, piloted with Master of Public Health (MPH) students in April, 2019 at Thomas Jefferson University. Preceding and following the workshop, evaluation forms were used to assess participants' knowledge about Design Thinking concepts and attitudes towards the workshop experience. Metrics were aligned with established learning objectives related to process, impact, and outcomes of the workshop. We hypothesized that the workshop intervention would increase participants understanding of Design Thinking concepts and applications in public health. Evaluations demonstrated that after attending the workshop, participants were able to understand and apply Design Thinking concepts in a public health context. Following the evaluation of pilot data, the workshop was refined and embedded in the MPH curriculum at Thomas Jefferson University in Philadelphia, PA.

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Dynamic minimum set problem for reserve design: Heuristic solutions for large problems.

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Dynamic minimum set problem for reserve design: Heuristic solutions for large problems.

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