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Relevant bibliographies by topics / Planning Problem solving

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Academic literature on the topic 'Planning Problem solving'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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Journal articles on the topic "Planning Problem solving"

1

Strohschneider, Stefan, and Dominik GÜss. "Planning and Problem Solving." Journal of Cross-Cultural Psychology 29, no. 6 (November 1998): 695–716. http://dx.doi.org/10.1177/0022022198296002.

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Anderson, Rita. "Planning and problem solving." Cancer Nursing 15, no. 1 (February 1992): 34???39. http://dx.doi.org/10.1097/00002820-199202000-00005.

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Hunt, Dennis, Philip R. de Lacey, and Bikkar S. Randhawa. "Problem Solving, Planning and Personality." International Journal of Psychology 22, no. 1 (January 1987): 97–110. http://dx.doi.org/10.1080/00207598708246770.

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Nemani, Ashish K., Suat Bog, and Ravindra K. Ahuja. "Solving the Curfew Planning Problem." Transportation Science 44, no. 4 (November 2010): 506–23. http://dx.doi.org/10.1287/trsc.1100.0323.

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Gunzelmann, Glenn, and John R. Anderson. "Problem solving: Increased planning with practice." Cognitive Systems Research 4, no. 1 (March 2003): 57–76. http://dx.doi.org/10.1016/s1389-0417(02)00073-6.

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Barton Cunningham, J. "Leadership in Planning and Problem Solving." Leadership & Organization Development Journal 12, no. 4 (April 1991): 22–27. http://dx.doi.org/10.1108/01437739110006936.

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hasoon, safwan. "Rule Based Planning for Solving Hanoi Problem." AL-Rafidain Journal of Computer Sciences and Mathematics 10, no. 4 (December 1, 2013): 51–59. http://dx.doi.org/10.33899/csmj.2013.163546.

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Neely, Ann M. "Planning and Problem Solving in Teacher Education." Journal of Teacher Education 37, no. 3 (May 1986): 29–33. http://dx.doi.org/10.1177/002248718603700306.

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Davis, D. "Complete Dentures: From Planning to Problem Solving." British Dental Journal 196, no. 12 (June 2004): 786. http://dx.doi.org/10.1038/sj.bdj.4811392.

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Gauvain, Mary, and Barbara Rogoff. "Collaborative problem solving and children's planning skills." Developmental Psychology 25, no. 1 (1989): 139–51. http://dx.doi.org/10.1037/0012-1649.25.1.139.

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Dissertations / Theses on the topic "Planning Problem solving"

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Patel, Niranjani H. "A new approach to solving a multilocation distribution problem." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/24550.

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Weppenaar, D. V. I., and H. J. Vermaak. "Solving planning problems with Drools Planner a tutorial." Interim : Interdisciplinary Journal, Vol 10 , Issue 1: Central University of Technology Free State Bloemfontein, 2011. http://hdl.handle.net/11462/338.

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Published Article
Planning problems are frequently encountered in everyday situations. The brute force approach of evaluating every possible solution for any medium size planning problem is just not feasible. Drools Planner is an open source Java library developed to help solve planning problems by using meta-heuristic algorithms. Drools Planner uses the Drools Expert (rule engine) for score calculation to greatly reduce the complexity and effort required to write scalable constraints in a declarative manner. This paper presents an introduction to Drools Planner, how it can be used to solve problems and concludes with an example scenario.

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Håård, Fredrik. "Multi-Agent Diplomacy : Tactical Planning using Cooperative Distributed Problem Solving." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5118.

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While there is a broad theoretic foundation for creating artificial intelligence based solutions for two-player games, such as Chess, the multi-player domain is not as well explored and artificial intelligence solutions for multi-player games is often flawed. This report is an attempt to apply a multi-agent approach to a multi-player game, and use distributed problem solving to create viable plans in an environment of huge search spaces and multiple adversaries. An automated player (bot) for the game Diplomacy was created using distributed methodologies, and tested against other existing bots. The tests show that the bot developed can outperform opposition in score while being competetive in speed.

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Hoffmann, Jörg. "Utilizing problem structure in planning : a local search approach /." Berlin [u.a.] : Springer, 2003. http://www.loc.gov/catdir/enhancements/fy0818/2003065658-d.html.

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Cole, Bjorn Forstrom. "An evolutionary method for synthesizing technological planning and architectural advance." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29758.

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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Mavris, Dimitri; Committee Member: Costello, Mark; Committee Member: German, Brian. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Adelman, Allen. "Solving Boston Harbor's combined sewer overflow problem : is there room for innovation?" Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/71073.

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Ruh, Nina [Verfasser], and Markus [Akademischer Betreuer] Heinrichs. "Dissociable stages of planning and problem solving = Dissoziierbare Phasen im Planungs- und Problemlöseprozess." Freiburg : Universität, 2014. http://d-nb.info/1123478740/34.

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Davidson, Duncan. "Social problem solving, cognitive defusion and social identification in wellness recovery action planning." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33141.

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Objective: The concept of recovery has become an integral part of modern mental health care. Understanding the outcomes and underlying mechanisms of key recovery interventions, such as Wellness Recovery Action Planning (WRAP), is essential in order to expand the theoretical understanding of recovery and inform how to target recovery in treatment. Therefore a systematic review of the literature was conducted to evaluate the mental health outcomes of WRAP for adults. The empirical study then explored three constructs in relation to WRAP and recovery. These were social problem solving, cognitive defusion and social identification. Method: The systematic review of the mental health outcomes of WRAP was conducted by searching four databases, contacting the authors of WRAP research and seeking evaluative information from organisations that deliver WRAP. Fourteen relevant studies met the inclusion criteria. Whereas, the empirical study recruited participants on a trans-diagnostic basis from across Scotland. Using a quantitative cross sectional design, 109 participant's completed 5 self-report questionnaires. These were the Knowledge, Attitudes and Beliefs about WRAP Questionnaire (WRAP beliefs), the Recovery Assessment Scale - Short (RAS-S), the Social Problem Solving Inventory - Revised - Short (SPSI-R-S), the Four Item Measure of Social Identification (FISI) and the Cognitive Fusion Questionnaire (CFQ). Correlation, regression and mediation analysis were used to explore relationships, and in particular, the predictors and mediators of recovery. Results: The systematic review provided strong evidence that WRAP has a significant positive impact on hope and also reduces the symptoms of mental illness. However, whether WRAP improves personal levels of recovery was unclear and a possible risk of disempowerment was found. Promising preliminary mental health outcomes in the areas of confidence in managing mental health, quality of life, service use, self-advocacy and knowledge attitudes and beliefs about recovery were highlighted. Only studies that did not use peer facilitators failed to find significant increases in hope compared to treatment as usual control groups. In the empirical study, the results indicated that all the constructs examined were correlated to recovery. In the regression analysis, WRAP beliefs, social problem solving and cognitive defusion also demonstrated a predictive relationship with recovery. Mediation analysis indicated that, social problem solving mediated two distinct relationships. One between WRAP beliefs and recovery, and another between cognitive defusion and recovery. The social problem solving subscales also showed how the two predictors relate to recovery through social problem solving in different ways. Social identification with the WRAP group did not significantly predict or mediate recovery. Conclusions: The systematic review indicated having peer facilitators delivering WRAP is key to helping participants foster hope and that a further randomised control trial could help clarify if improved personal recovery is an outcome of WRAP. It additionally suggested how the relationship between WRAP beliefs and recovery could be explored, as per the design of the empirical study. Findings from the empirical study implied that improving participants' social problem solving and cognitive defusion should be specifically targeted in WRAP delivery. The studies combined indicate that to achieve the best recovery results interventions, like WRAP, should target inspiring hope through peer support, improving knowledge, attitudes and beliefs about recovery and cognitive defusion from unhelpful thoughts.

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Li, Huaming. "Reasoning about actions and plans in artificial intelligence and engineering." Thesis, University of Bristol, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385690.

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Elliott-Ortega, Kara. "Urban design as problem solving : design thinking in the rebuild by design resiliency competition." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98931.

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Thesis: M.C.P., Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 124-129).
Following Hurricane Sandy in 2012, federal, state, and local governments initiated a series of disaster relief and recovery programs. These efforts were criticized for their lack of coordination, and fueled the public opinion that not only were coastal cities increasingly at risk for storm events due to climate change, but also that the government is not equipped to adequately respond to or prevent future disasters. The Rebuild by Design urban design competition was the first implemented recommendation of the cabinet-level Hurricane Sandy Rebuilding Task Force, and the main goal for the competition was the procurement of innovative resiliency projects for the areas affected by Hurricane Sandy. Sponsored by the U.S. Department of Housing and Urban Development (HUD), the competition is an unprecedented use of urban design by the federal government, leading to the question of why HUD would turn to an urban design process in the midst of other recovery efforts. Through interviews with designers from the winning design teams, this thesis finds that design thinking, under-examined by the participants, management, and evaluations of the competition, is the underlying theory that explains the benefits of an urban design process in the context of responding to climate change. Design thinking theorizes design as an alternative decision making process that can address complex problems for which there is no correct solution. This leads to the use of design as a method of creative problem solving as well as a catalyst for organizational change. This thesis finds that the competition design teams practice characteristics of design thinking. The resulting design ideas synthesize across regional, social, and economic systems, and offer an improved approach to the current infrastructure practices of flood protection and water mitigation. At the same time, the ability of the design process to fulfill the organizational goals of the competition, such as capacity building for local governments, remains mixed. Finally, this thesis generates recommendations for future iterations of Rebuild by Design as well as cautionary lessons for designers in light of the politics of relying on design as a form of innovation.
by Kara Elliott-Ortega.
M.C.P.

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Books on the topic "Planning Problem solving"

1

E, Baker Thomas. Positive police leadership: Problem-solving planning. Flushing, NY: Looseleaf Law Publications, 2012.

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Frank, Fletcher, ed. Solutions: Business problem solving. Burlington, VT: Gower Pub., 2011.

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Planning cash flow: A problem-solving approach. New York: American Management Association, 1986.

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Thierauf, Robert J. A problem-finding approach to effective corporate planning. New York: Quorum Books, 1987.

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Dunning, C. Mark. Collaborative problem solving for installation planning and decision making. Fort Belvoir, VA: US Army Corps of Engineers, Engineer Institute for Water Resources, 1986.

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Pearpoint, Jack. PATH: A workbook for planning positive possible futures : planning alternative tomorrows with hope : for schools, organizations, businesses, families. 2nd ed. Toronto: Inclusion Press, 1993.

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Six disciplines execution revolution: Solving the one business problem that makes solving all other problems easier. Findlay, Ohio: Six Disciplines Pub., 2008.

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Harpst, Gary. Six disciplines execution revolution: Solving the one business problem that makes solving all other problems easier. Findlay, Ohio: Six Disciplines Pub., 2008.

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Sustaining continuous innovation through problem solving. New York: Industrial Press, 2008.

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Ben-Ayed, Omar. Solving a real world highway network design problem using bilevel linear programming. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1988.

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Book chapters on the topic "Planning Problem solving"

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Durfee, Edmund H. "Planning Local Problem Solving." In The Kluwer International Series in Engineering and Computer Science, 67–110. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1699-2_4.

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Thornton, Stephanie. "Planning and Problem Solving." In Growing Minds, 126–50. London: Macmillan Education UK, 2002. http://dx.doi.org/10.1007/978-1-137-05456-2_6.

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Durfee, Edmund H. "Distributed Problem Solving and Planning." In Multi-Agent Systems and Applications, 118–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-47745-4_6.

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Grigg, Neil S. "Planning for Integrative Problem-Solving." In Integrated Water Resource Management, 67–98. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-57615-6_4.

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Adams, Bridget, and Barbara Bromley. "Planning, playing and problem-solving." In Psychology for Health Care, 246–62. London: Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-26634-0_16.

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Gaglio, Salvatore, Maurizio Cardaci, Ingrid Isenhardt, Dietrich Brandt, and Giuseppe Strina. "Panel Summary: Planning and Problem Solving." In Human and Machine Perception 2, 125–35. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4809-6_12.

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Parkin, Jason R., and Ashli D. Tyre. "Planning and Facilitating Problem-Solving Meetings." In Facilitating Effective Communication in School-Based Meetings, 82–118. New York: Routledge, 2021. http://dx.doi.org/10.4324/9780367854522-5-5.

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Haas, Olivier Cyrille Louis. "Solving the Inverse Problem in Radiotherapy Treatment Planning." In Radiotherapy Treatment Planning, 91–134. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0821-4_4.

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Zhou, Neng-Fa, Håkan Kjellerstrand, and Jonathan Fruhman. "Encodings for the Traveling Salesman Problem." In Constraint Solving and Planning with Picat, 129–39. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25883-6_7.

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Valle, Carmelo Del, Rafael M. Gasca, Miguel Toro, and Eduardo F. Camacho. "A Genetic Algorithm for Assembly Sequence Planning." In Artificial Neural Nets Problem Solving Methods, 337–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44869-1_43.

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Conference papers on the topic "Planning Problem solving"

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Shaorui Li and M. Kubo. "Modeling and Solving the Practical Production Planning Problem." In 2009 International Conference on Computer and Automation Engineering. ICCAE 2009. IEEE, 2009. http://dx.doi.org/10.1109/iccae.2009.21.

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Bryan, A., S. J. Hu, and Y. Koren. "Methodology for Solving the Assembly System Reconfiguration Planning Problem." In ASME 2011 International Manufacturing Science and Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/msec2011-50089.

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The need to cost effectively introduce new generations of product families within ever decreasing time frames have led manufacturers to seek product development strategies with a multigenerational outlook. Co-evolution of product families and assembly systems is a methodology that leads to the simultaneous design of several generations of product families and reconfigurable assembly systems that optimize life cycle costs. Two strategies that are necessary for the implementation of the co-evolution of product families and assembly systems methodology are: (1) The concurrent design of product families and assembly systems and (2) Assembly system reconfiguration planning (ASRP). ASRP is used for the determination of the assembly system reconfiguration plans that minimize the cost of producing several generations of product families. More specifically, the objective of ASRP is to minimize the net present cost of producing successive generations of products. This paper introduces a method for finding optimum solutions to the ASRP problem. The solution methodology involves the generation of a staged network of assembly system plans for all the generations that the product family is expected to be produced. Each stage in the network represents a generation that the product family is produced, while each state within a stage represents a potential assembly system configuration. A novel algorithm for generating the states (i.e. assembly system configurations) within each generation is also introduced. A dynamic program is used to find the cost minimizing path through the network. An example is used to demonstrate the implementation of the ASRP methodology.

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Ming, Kong. "Solving path planning problem based on ant colony algorithm." In 2017 29th Chinese Control And Decision Conference (CCDC). IEEE, 2017. http://dx.doi.org/10.1109/ccdc.2017.7979455.

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Li, Haitao, Sujian Li, and Di Wu. "Solving Hot Rolling Batch Planning Problem by Genetic Algorithm." In 2011 International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2011. http://dx.doi.org/10.1109/iciii.2011.267.

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Karray, F., E. Zaneldin, T. Hegazy, A. Shabeeb, and E. Elbeltagi. "Computational intelligence tools for solving the facilities layout planning problem." In Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.876964.

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Wen-Xiang Gu, Jin-Li Li, Ming-Hao Yin, Jun-Shu Wang, and Jin-Yan Wang. "A novel causal graph based heuristic for solving planning problem." In 2008 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2008. http://dx.doi.org/10.1109/icmlc.2008.4620775.

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Buzdalov, Maxim, and Andrey Sokolov. "Evolving EFSMs solving a path-planning problem by genetic programming." In the fourteenth international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2330784.2330880.

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Sylejmani, Kadri, Atdhe Muhaxhiri, Agni Dika, and Lule Ahmedi. "Solving tourist trip planning problem via a simulated annealing algorithm." In 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 2014. http://dx.doi.org/10.1109/mipro.2014.6859737.

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Seok, Joon-Hong, Joon-Woo Lee, Jeong-Hyun Wang, Ju-Jang Lee, and Ho Joo Lee. "Multi-layered integrated path planning for solving path mismatch problem." In 2012 IEEE/SICE International Symposium on System Integration (SII 2012). IEEE, 2012. http://dx.doi.org/10.1109/sii.2012.6427275.

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Ghambari, Soheila, Lhassane Idoumghar, Laetitia Jourdan, and Julien Lepagnot. "An Improved TLBO Algorithm for Solving UAV Path Planning Problem." In 2019 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2019. http://dx.doi.org/10.1109/ssci44817.2019.9003160.

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Reports on the topic "Planning Problem solving"

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Srinivasan, C. V. The Use of CK-LOG Formalism for Knowledge Representation and Problem Solving in OPPLAN-CONSULTANT: An Expert System for Naval Operational Planning. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada160999.

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Singh, Kavinesh J., Andy B. Philpott, and R. K. Wood. Dantzig-Wolfe Decomposition for Solving Multi-Stage Stochastic Capacity-Planning Problems. Fort Belvoir, VA: Defense Technical Information Center, July 2005. http://dx.doi.org/10.21236/ada486953.

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