Relevant bibliographies by topics / Constraint programming

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Constraint programming'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Constraint programming"

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APT, KRZYSZTOF R., and ERIC MONFROY. "Constraint programming viewed as rule-based programming." Theory and Practice of Logic Programming 1, no. 6 (2001): 713–50. http://dx.doi.org/10.1017/s1471068401000072.

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We study here a natural situation when constraint programming can be entirely reduced to rule-based programming. To this end we explain first how one can compute on constraint satisfaction problems using rules represented by simple first-order formulas. Then we consider constraint satisfaction problems that are based on predefined, explicitly given constraints. To solve them we first derive rules from these explicitly given constraints and limit the computation process to a repeated application of these rules, combined with labeling. We consider two types of rule here. The first type, that we
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Van Hentenryck, Pascal, Laurent Michel, and Frédéric Benhamou. "Constraint programming over nonlinear constraints." Science of Computer Programming 30, no. 1-2 (1998): 83–118. http://dx.doi.org/10.1016/s0167-6423(97)00008-7.

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O'Sullivan, Barry. "Automated Modelling and Solving in Constraint Programming." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 1493–97. http://dx.doi.org/10.1609/aaai.v24i1.7530.

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Constraint programming can be divided very crudely into modeling and solving. Modeling defines the problem, in terms of variables that can take on different values, subject to restrictions (constraints) on which combinations of variables are allowed. Solving finds values for all the variables that simultaneously satisfy all the constraints. However, the impact of constraint programming has been constrained by a lack of "user-friendliness''. Constraint programming has a major "declarative" aspect, in that a problem model can be handed off for solution to a variety of standard solving methods. T
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Dao, Thi-Bich-Hanh, Khanh-Chuong Duong, and Christel Vrain. "Constrained clustering by constraint programming." Artificial Intelligence 244 (March 2017): 70–94. http://dx.doi.org/10.1016/j.artint.2015.05.006.

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SCHRIJVERS, TOM, PETER STUCKEY, and PHILIP WADLER. "Monadic constraint programming." Journal of Functional Programming 19, no. 6 (2009): 663–97. http://dx.doi.org/10.1017/s0956796809990086.

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AbstractA constraint programming system combines two essential components: a constraint solver and a search engine. The constraint solver reasons about satisfiability of conjunctions of constraints, and the search engine controls the search for solutions by iteratively exploring a disjunctive search tree defined by the constraint program. In this paper we give a monadic definition of constraint programming in which the solver is defined as a monad threaded through the monadic search tree. We are then able to define search and search strategies as first-class objects that can themselves be buil
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Mattenet, Alex, Ian Davidson, Siegfried Nijssen, and Pierre Schaus. "Generic Constraint-based Block Modeling using Constraint Programming." Journal of Artificial Intelligence Research 70 (February 9, 2021): 597–630. http://dx.doi.org/10.1613/jair.1.12280.

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Block modeling has been used extensively in many domains including social science, spatial temporal data analysis and even medical imaging. Original formulations of the problem modeled it as a mixed integer programming problem, but were not scalable. Subsequent work relaxed the discrete optimization requirement, and showed that adding constraints is not straightforward in existing approaches. In this work, we present a new approach based on constraint programming, allowing discrete optimization of block modeling in a manner that is not only scalable, but also allows the easy incorporation of c
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Dincbas, M. "Constraint programming." ACM Computing Surveys 28, no. 4es (1996): 62. http://dx.doi.org/10.1145/242224.242303.

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Van Hentenryck, Pascal. "Constraint Programming." Revue Ouverte d'Intelligence Artificielle 5, no. 2-3 (2024): 139–59. http://dx.doi.org/10.5802/roia.76.

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Van Hentenryck, Pascal. "Constraint programming." ACM SIGSOFT Software Engineering Notes 25, no. 1 (2000): 89–90. http://dx.doi.org/10.1145/340855.341036.

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Booth, Kyle E. C., Bryan O'Gorman, Jeffrey Marshall, Stuart Hadfield, and Eleanor Rieffel. "Quantum-accelerated constraint programming." Quantum 5 (September 28, 2021): 550. http://dx.doi.org/10.22331/q-2021-09-28-550.

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Constraint programming (CP) is a paradigm used to model and solve constraint satisfaction and combinatorial optimization problems. In CP, problems are modeled with constraints that describe acceptable solutions and solved with backtracking tree search augmented with logical inference. In this paper, we show how quantum algorithms can accelerate CP, at both the levels of inference and search. Leveraging existing quantum algorithms, we introduce a quantum-accelerated filtering algorithm for the alldifferent global constraint and discuss its applicability to a broader family of global constraints
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Dissertations / Theses on the topic "Constraint programming"

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Duong, Khanh-Chuong. "Constrained clustering by constraint programming." Thesis, Orléans, 2014. http://www.theses.fr/2014ORLE2049/document.

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La classification non supervisée, souvent appelée par le terme anglais de clustering, est une tâche importante en Fouille de Données. Depuis une dizaine d'années, la classification non supervisée a été étendue pour intégrer des contraintes utilisateur permettant de modéliser des connaissances préalables dans le processus de clustering. Différents types de contraintes utilisateur peuvent être considérés, des contraintes pouvant porter soit sur les clusters, soit sur les instances. Dans cette thèse, nous étudions le cadre de la Programmation par Contraintes (PPC) pour modéliser les tâches de clu
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Achterberg, Tobias. "Constraint integer programming /." München : Verl. Dr. Hut, 2008. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017108806&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Achterberg, Tobias. "Constraint integer programming." München Verl. Dr. Hut, 2007. http://d-nb.info/992163366/04.

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Jefferson, Christopher. "Representations in constraint programming." Thesis, University of York, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445465.

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McDonald, Iain. "Symmetry in constraint programming." Thesis, University of St Andrews, 2004. http://hdl.handle.net/10023/14983.

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Constraint programming is an invaluable tool for solving many of the complex NP-complete problems that we need solutions to. These problems can be easily described as Constraint Satisfaction Problems (CSPs) and then passed to constraint solvers: complex pieces of software written to solve general CSPs efficiently. Many of the problems we need solutions to are real world problems: planning (e.g. vehicle routing), scheduling (e.g. job shop schedules) and timetabling problems (e.g. staff rotas) to name but a few. In the real world, we place structure on objects to make them easier to deal with. T
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Backeman, Peter. "Propagating the nVector Constraint : Haplotype Inference using Constraint Programming." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-211862.

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Genetics research is a wide field and needs computer aid in many different areas. One such problem is the haplotype inference problem by pure parsimony (HIPP). In this thesis the HIPP problem is attacked with a constraint programming (CP) model based on the nVector constraint, for which a new propagator is designed. The results show that the current state-of-the-art  model based on SAT-solvers are in general the most efficient, but that the CP approach in some cases finds a better  solution when time is limited.
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Hnich, Brahim. "Function Variables for Constraint Programming." Doctoral thesis, Uppsala University, Department of Information Science, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3143.

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<p>Quite often modelers with constraint programming (CP) use the same modelling patterns for different problems, possibly from different domains. This results in recurring idioms in constraint programs. Our approach can be seen as a three-step approach. First, we identify some of these recurring patterns in constraint programs. Second, we propose a general way of describing these patterns by introducing proper constructs that would cover a wide range of applications. Third, we propose automating the process of reproducing these idioms from these higher-level descriptions. The whole process c
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Jägare, Peter. "Airspace Sectorisation using Constraint Programming." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155783.

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Given a set of cells and a set of flight routes passing through these cells, we need to cluster cells into a given number of sectors, ensuring an even workload over all sectors, and fulfilling several other constraints on the wellformedness of sectors. The sectorisation is done by using constraint programming. Several propagators are designed to ensure the correctness of the sectorisation.
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Olive, Xavier. "Symmetries in Distributed Constraint Programming." 京都大学 (Kyoto University), 2011. http://hdl.handle.net/2433/142134.

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Wetsel, Gerhard. "Abductive and constraint logic programming." Thesis, Imperial College London, 1997. http://hdl.handle.net/10044/1/7212.

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Books on the topic "Constraint programming"

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Mayoh, Brian, Enn Tyugu, and Jaan Penjam, eds. Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0.

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Schulte, Christian, ed. Programming Constraint Services. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45945-6.

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Saraswat, Vijay. Concurrent constraint programming. MIT Press, 1993.

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Achterberg, Tobias. Constraint integer programming. Verl. Dr. Hut, 2007.

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Apt, Krzysztof R. Principles of constraint programming. Cambridge University Press, 2010.

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Assayag, Gérard, and Charlotte Truchet. Constraint programming in music. John Wiley & Sons, 2011.

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Frédéric, Benhamou, Jussien Narendra, and O'Sullivan B, eds. Trends in constraint programming. ISTE USA, 2007.

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Frühwirth, Thom. Essentials of Constraint Programming. Springer Berlin Heidelberg, 2003.

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Benhamou, Frdric, Narendra Jussien, and Barry O'Sullivan, eds. Trends in Constraint Programming. ISTE, 2007. http://dx.doi.org/10.1002/9780470612309.

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Hofstedt, Petra. Multiparadigm Constraint Programming Languages. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17330-1.

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Book chapters on the topic "Constraint programming"

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Borning, Alan, Bjorn Freeman-Benson, and Molly Wilson. "Constraint Hierarchies." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_4.

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Mayoh, Brian, Enn Tyugu, and Tarmo Uustalu. "Constraint Satisfaction and Constraint Programming: A Brief Lead-In." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_1.

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Palmgren, Erik. "Denotational Semantics of Constraint Logic Programming — A Nonstandard Approach." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_10.

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Mints, Grigori. "Resolution Strategies for the Intuitionistic Logic." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_11.

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Lopez, Gus, Bjorn Freeman-Benson, and Alan Borning. "Kaleidoscope: A Constraint Imperative Programming Language." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_12.

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Penjam, Jaan, and Enn Tyugu. "Constraints in NUT." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_13.

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Hyvőnen, Eero, Stefano De Pascale, and Aarno Lehtola. "Interval Constraint Programming in C++." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_14.

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Saraswat, Vijay, Radha Jagadeesan, and Vinheet Gupta. "Programming in Timed Concurrent Constraint Languages." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_15.

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Janson, Sverker, and Seif Haridi. "An Introduction to AKL A Multi-Paradigm Programming Language." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_16.

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Mayoh, Brian. "Constraint Programming and Artificial Intelligence." In Constraint Programming. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_2.

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Conference papers on the topic "Constraint programming"

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Régin, Florian, and Elisabetta De Maria. "Generative Constraint Programming Revisited." In 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2024. https://doi.org/10.1109/ictai62512.2024.00012.

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Roisin, Mathieu, Pierre-Alain Yvars, and Bernard Riera. "Constraint Programming for Logic controller Synthesis." In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2024. http://dx.doi.org/10.1109/codit62066.2024.10708360.

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Garreau, Bryan, Martin Dieguez Lodeiro, Eric Monfroy, and Igor Stéphan. "Introducing Constraint Well-Founded Semantics for Constraint Logic Programming Through Rewriting Transformations." In 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2024. https://doi.org/10.1109/ictai62512.2024.00062.

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Karacan, Kübra, Robin Jeanne Kirschner, Hamid Sadeghian, Fan Wu, and Sami Haddadin. "Tactile Robot Programming: Transferring Task Constraints into Constraint-Based Unified Force-Impedance Control." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610054.

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Jaffar, J., and J. L. Lassez. "Constraint logic programming." In the 14th ACM SIGACT-SIGPLAN symposium. ACM Press, 1987. http://dx.doi.org/10.1145/41625.41635.

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Jagadeesan, Radha, and Will Marrero. "Timed constraint programming." In the 7th ACM SIGPLAN international conference. ACM Press, 2005. http://dx.doi.org/10.1145/1069774.1069790.

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Di Pierro, Alessandra, and Herbert Wiklicky. "Concurrent constraint programming." In the 2nd ACM SIGPLAN international conference. ACM Press, 2000. http://dx.doi.org/10.1145/351268.351284.

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Saraswat, Vijay A., and Martin Rinard. "Concurrent constraint programming." In the 17th ACM SIGPLAN-SIGACT symposium. ACM Press, 1990. http://dx.doi.org/10.1145/96709.96733.

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Pothitos, Nikolaos, and Panagiotis Stamatopoulos. "Constraint Programming MapReduce'd." In SETN '16: 9th Hellenic Conference on Artificial Intelligence. ACM, 2016. http://dx.doi.org/10.1145/2903220.2903248.

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Hemmi, David. "Stochastic Constraint Programming." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/751.

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Combinatorial optimisation problems often contain uncertainty that has to be taken into account to pro- duce realistic solutions. One way of describing the uncertainty is using scenarios, where each sce- nario describes different potential sets of problem parameters based on random distributions or his- torical data. While efficient algorithmic techniques exist for specific problem classes such as linear pro- grams, there are very few approaches that can han- dle general Constraint Programming formulations with uncertainty. The goal of my PhD is to develop generic methods for solving stochasti
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Reports on the topic "Constraint programming"

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Gupta, Nitesh. Constraint Programming Using Multi-Valued Decision Diagrams. Iowa State University, 2019. http://dx.doi.org/10.31274/cc-20240624-418.

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BROWN UNIV PROVIDENCE RI. Workshop on Principles and Practice of Constraint Programming (1st) Held in Newport, Rhode Island on 28-30 April 1993. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada281201.

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Ait-Kaci, Hassan, and Andreas Podelski. Position Papers for the First Workshop on Principles and Practice of Constraint Programming Held in Newport, Rhode Island on April 28-30, 1993. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada281497.

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Ariyawansa, K. A., and Yuntao Zhu. Chance-Constrained Semidefinite Programming. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada530454.

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Day, William B. Constraints Logic Programming in Knowledge-Based Planning Domains. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada262958.

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VAN BLOEMEN WAANDERS, BART G., ROSCOE A. BARTLETT, KEVIN R. LONG, PAUL T. BOGGS, and ANDREW G. SALINGER. Large Scale Non-Linear Programming for PDE Constrained Optimization. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/805833.

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Boggs, P. T., J. W. Tolle, and A. J. Kearsley. A merit function for inequality constrained nonlinear programming problems. National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.ir.4702.

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Dennis, John E., Tapia Jr., Torczon Richard A., and Virginia J. Some Issues in Nonlinear Programming Algorithms for Problems with Simulation Constraints. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada294932.

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Thorpe, Jodie, Alisha Ault, Iana Barenboim, Luize Guimarães, Evert-jan Quak, and Katia Taela. Learning from Entrepreneurship Programming for Women’s Economic Empowerment. Institute of Development Studies, 2023. http://dx.doi.org/10.19088/muva.2023.001.

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MUVA is a social incubator dedicated to developing innovative approaches to the economic empowerment of women in Mozambique. This paper documents experiences from two MUVA projects supporting women’s economic empowerment through entrepreneurship, and draws out broader insights and principles of relevance to other similar programmes. Barriers to women’s economic empowerment and strategies to overcome these barriers are both individual and systemic, visible and invisible. MUVA’s approach to supporting women’s economic empowerment through entrepreneurship involves tailoring three core elements to
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Sembler, Jose Ignacio, Diether Beuermann, Carlos Elías, and Cheryl Gray. IDB-9: Country Programming. Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0010515.

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This paper analyzes whether IDB-9 requirements surrounding the country programming process of the Inter-American Development Bank (IDB, or Bank) are being implemented fully and effectively. The country programming process includes two documents: the Country Strategy, which provides a multiyear overview of the Bank¿s work program; and an annual document that lays out lending allocations and the work program. The main requirements of IDB-9 related to country programming are that Country Strategies include development and macro-fiscal frameworks, that they build on these frameworks and country di
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