scholarly journals Practical problem solving with cutting plane algorithms in combinatorial optimization

1995 ◽  
pp. 111-152 ◽  
Author(s):  
M Junger ◽  
G Reinelt ◽  
Stefan Thienel
Keyword(s):  
Combinatorial Optimization ◽  
Problem Solving ◽  
Practical Problem ◽  
Cutting Plane ◽  
Cutting Plane Algorithms

Boosting branch-and-bound MaxSAT solvers with clause learning

2021 ◽  
pp. 1-21
Author(s):  
Chu-Min Li ◽  
Zhenxing Xu ◽  
Jordi Coll ◽  
Felip Manyà ◽  
Djamal Habet ◽  
...  
Keyword(s):  
Experimental Investigation ◽  
Combinatorial Optimization ◽  
Problem Solving ◽  
Branch And Bound ◽  
Real World ◽  
Optimization Problems ◽  
Satisfiability Problem ◽  
Maximum Satisfiability ◽  
Combinatorial Optimization Problems ◽  
Clause Learning

The Maximum Satisfiability Problem, or MaxSAT, offers a suitable problem solving formalism for combinatorial optimization problems. Nevertheless, MaxSAT solvers implementing the Branch-and-Bound (BnB) scheme have not succeeded in solving challenging real-world optimization problems. It is widely believed that BnB MaxSAT solvers are only superior on random and some specific crafted instances. At the same time, SAT-based MaxSAT solvers perform particularly well on real-world instances. To overcome this shortcoming of BnB MaxSAT solvers, this paper proposes a new BnB MaxSAT solver called MaxCDCL. The main feature of MaxCDCL is the combination of clause learning of soft conflicts and an efficient bounding procedure. Moreover, the paper reports on an experimental investigation showing that MaxCDCL is competitive when compared with the best performing solvers of the 2020 MaxSAT Evaluation. MaxCDCL performs very well on real-world instances, and solves a number of instances that other solvers cannot solve. Furthermore, MaxCDCL, when combined with the best performing MaxSAT solvers, solves the highest number of instances of a collection from all the MaxSAT evaluations held so far.

scholarly journals Students’ Perceptions on Practical Problem Solving in Mathematics in E-environment

2014 ◽  
Vol 4 (2) ◽  
pp. 47
Author(s):  
Anda Zeidmane ◽  
Vita Duka
Keyword(s):  
Problem Solving ◽  
Practical Problem ◽  
Learning System ◽  
Basic Knowledge ◽  
Mathematics Students ◽  
Problem Solving Skills ◽  
Survey Results ◽  
Study Process ◽  
Time To Learn ◽  
Computerized Learning

Study process in mathematics faces two major problems. First, engineers do not apply directly the problem solving skills of higher mathematics. Second, studying higher mathematics, students get an insufficient idea of its usability. The authors of the paper have worked out frameworks for practical problem solving in mathematics on the basis of didactic ontology in the Moodle computerized learning system (CMS. To determine students' perceptions on practical problem solving in mathematics in e-environment, more than 300 students from the specialties of engineering at the LUA participated in the survey. The survey results showed many students lack basic knowledge in mathematics, therefore they consume a lot of time to learn the basics in higher mathematics and to acquire the skills of practical problem solving in mathematics are less important.

Sign in / Sign up

Export Citation Format

Share Document