| 1. |
- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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| 2. |
- Niemi, MEK, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 3. |
- Shahim, Bahira, et al.
(författare)
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On-Treatment Platelet Reactivity and Ischemic Outcomes in Patients With Diabetes Mellitus: Two-Year Results From ADAPT-DES.
- 2022
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Ingår i: Journal of the American Heart Association. - 2047-9980.
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Tidskriftsartikel (refereegranskat)abstract
- Background Diabetes mellitus and high platelet reactivity (HPR) on clopidogrel are both associated with increased risk of ischemic events after percutaneous coronary intervention, but whether the HPR-associated risk of adverse ischemic events differs by diabetes mellitus status is unknown. Methods and Results ADAPT-DES (Assessment of Dual Antiplatelet Therapy With Drug-Eluting Stents) was a prospective, multicenter registry of patients treated with coronary drug-eluting stents. HPR was defined as P2Y12 reaction units >208 by the VerifyNow point-of-care assay. Cox multivariable analysis was used to assess whether HPR-associated risk of major adverse cardiac events (MACE; cardiac death, myocardial infarction, or stent thrombosis) varied for patients with insulin-treated diabetes mellitus (ITDM), non-ITDM, and no diabetes mellitus. Diabetes mellitus and HPR were included in an interaction analysis. Of 8582 patients enrolled, 2429 (28.3%) had diabetes mellitus, of whom 998 (41.1%) had ITDM. Mean P2Y12 reaction units were higher in patients with diabetes mellitus versus without diabetes mellitus, and HPR was more frequent in patients with diabetes mellitus. HPR was associated with consistently increased 2-year rates of MACE in patients with and without diabetes mellitus (Pinteraction=0.36). A significant interaction was present between HPR and non-insulin-treated diabetes mellitus versus ITDM for 2-year MACE (adjusted hazard ratio [HR] for non-ITDM, 2.28 [95% CI, 1.39-3.73] versus adjusted HR for ITDM, 1.02 [95% CI, 0.70-1.50]; Pinteraction=0.01). Conclusions HPR was more common in patients with diabetes mellitus and was associated with an increased risk of MACE in both patients with and without diabetes mellitus. In patients with diabetes mellitus, a more pronounced effect of HPR on MACE was present in lower-risk non-ITDM patients than in higher-risk patients with ITDM. Registration URL: https://clinicaltrials.gov/ct2/show/NCT00638794; Unique identifier: NCT00638794. ADAPT-DES (Assessment of Dual Antiplatelet Therapy With Drug-Eluting Stents).
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| 4. |
- Amadini, Roberto, et al.
(författare)
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MiniZinc with strings
- 2017
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Ingår i: Logic-Based Program Synthesis and Transformation. - Cham : Springer. - 9783319631387 - 9783319631394 ; , s. 59-75
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Konferensbidrag (refereegranskat)abstract
- Strings are extensively used in modern programming languages and constraints over strings of unknown length occur in a wide range of real-world applications such as software analysis and verification, testing, model checking, and web security. Nevertheless, practically no constraint programming solver natively supports string constraints. We introduce string variables and a suitable set of string constraints as builtin features of the MiniZinc modelling language. Furthermore, we define an interpreter for converting a MiniZinc model with strings into a FlatZinc instance relying only on integer variables. This conversion is obtained via rewrite rules, and does not require any extension of the existing FlatZinc specification. This provides a user-friendly interface for modelling combinatorial problems with strings, and enables both string and non-string solvers to actually solve such problems.
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| 5. |
- Björdal, Gustav, et al.
(författare)
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Declarative local-search neighbourhoods in MiniZinc
- 2018
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Ingår i: PROCEEDINGS OF THE 2018 IEEE 30TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI). - : IEEE Computer Society. - 9781538674499 ; , s. 98-105
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Konferensbidrag (refereegranskat)abstract
- The aim of solver-independent modelling is to create a model of a satisfaction or optimisation problem independent of a particular technology. This avoids early commitment to a solving technology and allows easy comparison of technologies. MiniZinc is a solver-independent modelling language, supported by CP, MIP, SAT, SMT, and constraint-based local search (CBLS) backends. Some technologies, in particular CP and CBLS, require not only a model but also a search strategy. While backends for these technologies offer default search strategies, it is often beneficial to include in a model a user-specified search strategy for a particular technology, especially if the strategy can encapsulate knowledge about the problem structure. This is complex since a local-search strategy (comprising a neighbourhood, a heuristic, and a meta-heuristic) is often tightly tied to the model. Hence we wish to use the same language for specifying the model and the local search. We show how to extend MiniZinc so that one can attach a fully declarative neighbourhood specification to a model, while maintaining the solver-independence of the language. We explain how to integrate a model-specific declarative neighbourhood with an existing CBLS backend for MiniZinc.
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| 6. |
- Björdal, Gustav, 1991-, et al.
(författare)
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Exploring declarative local-search neighbourhoods with constraint programming
- 2019
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Ingår i: Principles and Practice of Constraint Programming. - Switzerland : Springer. - 9783030300470 - 9783030300487 ; , s. 37-53
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Konferensbidrag (refereegranskat)abstract
- Using constraint programming (CP) to explore a local-search neighbourhood was first tried in the mid 1990s. The advantage is that constraint propagation can quickly rule out uninteresting neighbours, sometimes greatly reducing the number actually probed. However, a CP model of the neighbourhood has to be handcrafted from the model of the problem: this can be difficult and tedious. That research direction appears abandoned since large-neighbourhood search (LNS) and constraint-based local search (CBLS) arose as alternatives that seem easier to use. Recently, the notion of declarative neighbourhood was added to the technology-independent modelling language MiniZinc, for use by any backend to MiniZinc, but currently only used by a CBLS backend. We demonstrate that declarative neighbourhoods are indeed technology-independent by using the old idea of CP-based neighbourhood exploration: we explain how to encode automatically a declarative neighbourhood into a CP model of the neighbourhood. This enables us to lift any CP solver into a local-search backend to MiniZinc. Our prototype is competitive with CP, CBLS, and LNS backends to MiniZinc.
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| 7. |
- Björdal, Gustav, 1991-, et al.
(författare)
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Solving Satisfaction Problems using Large-Neighbourhood Search
- 2020
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Ingår i: Principles and Practice of Constraint Programming. - Cham : Springer International Publishing. - 9783030584740 - 9783030584757 ; , s. 55-71
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Konferensbidrag (refereegranskat)abstract
- Large-neighbourhood search (LNS) improves an initial solution, hence it is not directly applicable to satisfaction problems. In order to use LNS in a constraint programming (CP) framework to solve satisfaction problems, we usually soften some hard-to-satisfy constraints by replacing them with penalty-function constraints. LNS is then used to reduce their penalty to zero, thus satisfying the original problem. However, this can give poor performance as the penalties rarely cause propagation and therefore do not drive each CP search, and by extension the LNS search, towards satisfying the replaced constraints until very late. Our key observation is that entirely replacing a constraint is often overkill, as the propagator for the replaced constraint could have performed some propagation without causing backtracking. We propose the notion of a non-failing propagator, which is subsumed just before causing a backtrack. We show that, by only making a few changes to an existing CP solver, any propagator can be made non-failing without modifying its code. Experimental evaluation shows that non-failing propagators, when used in conjunction with penalties, can greatly improve LNS performance compared to just having penalties. This allows us to leverage the power of the many sophisticated propagators that already exist in CP solvers, in order to use LNS for solving hard satisfaction problems and for finding initial solutions to hard-to-satisfy optimisation problems.
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| 8. |
- Chu, Geoffrey, et al.
(författare)
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Confidence-based Work Stealing in Parallel Constraint Programming
- 2009
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Ingår i: Fifteenth International Conference on Principles and Practice of Constraint Programming. - Berlin, Heidelberg : Springer Science+Business Media B.V.. - 9783642042430 - 3642042430 ; , s. 226-241
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Konferensbidrag (refereegranskat)abstract
- The most popular architecture for parallel search is work stealing: threads that have run out of work (nodes to be searched) steal from threads that still have work. Work stealing not only allows for dynamic load balancing, but also determines which parts of the search tree are searched next. Thus the place from where work is stolen has a dramatic effect on the efficiency of a parallel search algorithm. This paper examines quantitatively how optimal work stealing can be performed given an estimate of the relative solution densities of the subtrees at each search tree node and relates it to the branching heuristic strength. An adaptive work stealing algorithm is presented that automatically performs different work stealing strategies based on the confidence of the branching heuristic at each node. Many parallel depth-first search patterns arise naturally from this algorithm. The algorithm produces near perfect or super linear algorithmic efficiencies on all problems tested. Real speedups using 8 threads range from 7 times to super linear.
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| 9. |
- Ingmar, Linnea, et al.
(författare)
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Modelling Diversity of Solutions
- 2020
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Ingår i: Thirty-fourth AAAI Conference on Artificial Intelligence, the thirty-second innovative applications of artificial intelligence conference and the tenth AAAI symposium on educational advances in artificial intelligence. - : ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. ; , s. 1528-1535
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Konferensbidrag (refereegranskat)abstract
- For many combinatorial problems, finding a single solution is not enough. This is clearly the case for multi-objective optimization problems, as they have no single "best solution" and, thus, it is useful to find a representation of the non-dominated solutions (the Pareto frontier). However, it also applies to single objective optimization problems, where one may be interested in finding several (close to) optimal solutions that illustrate some form of diversity. The same applies to satisfaction problems. This is because models usually idealize the problem in some way, and a diverse pool of solutions may provide a better choice with respect to considerations that are omitted or simplified in the model. This paper describes a general framework for finding k diverse solutions to a combinatorial problem (be it satisfaction, single-objective or multi-objective), various approaches to solve problems in the framework, their implementations, and an experimental evaluation of their practicality.
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| 10. |
- Oxenstierna, Johan, et al.
(författare)
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Optimization of the Storage Location Assignment Problem Using Nested Annealing
- 2024
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Ingår i: Operations Research and Enterprise Systems : 11th International Conference, ICORES 2022, Virtual Event, February 3–5, 2022, and 12th International Conference, ICORES 2023, Lisbon, Portugal, February 19-21, 2023, Revised Selected Papers - 11th International Conference, ICORES 2022, Virtual Event, February 3–5, 2022, and 12th International Conference, ICORES 2023, Lisbon, Portugal, February 19-21, 2023, Revised Selected Papers. - 1865-0937 .- 1865-0929. - 9783031496615 - 9783031496622 ; 1985 CCIS, s. 220-244
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Konferensbidrag (refereegranskat)abstract
- The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) are then modified according to the assignments and solved. The model is graph-based and generalizes to any obstacle layout in two dimensions. We investigate whether optimization speed-ups are possible using methods such as cost approximation, rejection of samples with low approximate cost and restarts from local minima. Results demonstrate that these methods improve performance, with total travel-cost reductions of up to 30% within 8 h of CPU-time. We share a public repository with SLAP instances and corresponding benchmark results on the generalizable TSPLIB format.
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