scholarly journals Application of constraint programming techniques for structure prediction of lattice proteins with extended alphabets

1999 ◽  
Vol 15 (3) ◽  
pp. 234-242 ◽  
Author(s):  
R Backofen ◽  
S Will ◽  
E Bornberg-Bauer
Keyword(s):  
Constraint Programming ◽  
Structure Prediction ◽  
Programming Techniques ◽  
Lattice Proteins

scholarly journals A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems

2011 ◽  
Vol 21 (4) ◽  
pp. 733-744 ◽  
Author(s):  
Marlene Arangú ◽  
Miguel Salido
Keyword(s):  
Constraint Satisfaction ◽  
Constraint Programming ◽  
Real Life ◽  
Search Space ◽  
Constraint Satisfaction Problems ◽  
Fine Grained ◽  
Arc Consistency ◽  
Life Problems ◽  
Programming Techniques ◽  
Np Complete

A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems Constraint programming is a powerful software technology for solving numerous real-life problems. Many of these problems can be modeled as Constraint Satisfaction Problems (CSPs) and solved using constraint programming techniques. However, solving a CSP is NP-complete so filtering techniques to reduce the search space are still necessary. Arc-consistency algorithms are widely used to prune the search space. The concept of arc-consistency is bidirectional, i.e., it must be ensured in both directions of the constraint (direct and inverse constraints). Two of the most well-known and frequently used arc-consistency algorithms for filtering CSPs are AC3 and AC4. These algorithms repeatedly carry out revisions and require support checks for identifying and deleting all unsupported values from the domains. Nevertheless, many revisions are ineffective, i.e., they cannot delete any value and consume a lot of checks and time. In this paper, we present AC4-OP, an optimized version of AC4 that manages the binary and non-normalized constraints in only one direction, storing the inverse founded supports for their later evaluation. Thus, it reduces the propagation phase avoiding unnecessary or ineffective checking. The use of AC4-OP reduces the number of constraint checks by 50% while pruning the same search space as AC4. The evaluation section shows the improvement of AC4-OP over AC4, AC6 and AC7 in random and non-normalized instances.

scholarly journals A New QoS Routing Northbound Interface for SDN

2017 ◽  
Vol 5 (1) ◽  
pp. 92-115
Author(s):  
Siamak Layeghy ◽  
Farzaneh Pakzad ◽  
Marius Portmann
Keyword(s):  
Constraint Programming ◽  
Traffic Engineering ◽  
Qos Routing ◽  
Modelling Language ◽  
Routing Problem ◽  
Programming Techniques ◽  
Network Topologies ◽  
High Level ◽  
Basic Constraint ◽  
High Level Abstraction

In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.

Global Results Synthesis

2020 ◽  
pp. 165-175
Keyword(s):  
Linear Programming ◽  
Simulated Annealing ◽  
Tabu Search ◽  
Local Search ◽  
Constraint Programming ◽  
Cpu Time ◽  
Exact Approach ◽  
First Results ◽  
Programming Techniques ◽  
Portfolio Design

This chapter provides a global synthesis of the realized results by applying exact and approximate approaches on the portfolio design (PD) problem. The authors introduce an experimental analysis of best approaches based on linear programming and constraint programming techniques, according to the CPU time. Next, a global experiment synthesis of the best approximate approaches based on Simulated Annealing, IDWalk, Tabu Search, GWW, and VNS is realized according to the number of success and the CPU time. First results show that constraint programming with breaking all the detected symmetries is the best as an exact approach, VNS combined with simulated annealing is effective on non-trivial instances of the problem, and simulated annealing is the most effective as a simple local search.

scholarly journals Mixed-Integer and Constraint Programming Techniques for Mobile Robot Task Planning

2016 ◽  
Vol 1 (1) ◽  
pp. 500-507 ◽  
Author(s):  
Kyle E. C. Booth ◽  
Tony T. Tran ◽  
Goldie Nejat ◽  
J. Christopher Beck
Keyword(s):  
Mobile Robot ◽  
Constraint Programming ◽  
Mixed Integer ◽  
Task Planning ◽  
Programming Techniques ◽  
Robot Task
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