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An Original Constraint Based Approach for Solving over Constrained Problems [chapter]

J. -C. Régin, T. Petit, C. Bessière, J. -F. Puget
2000 Lecture Notes in Computer Science  
doi:10.1007/3-540-45349-0_46 fatcat:ltmelnttvneg5jf5s3cs335uya

Solving Over-Constrained Temporal Reasoning Problems Using Local Search [chapter]

Matthew Beaumont, John Thornton, Abdul Sattar, Michael Maher
2004 Lecture Notes in Computer Science  
performance to constraint weighting for the over-constrained problems.  ...  In this paper, we apply local search methods to overcome the deficiencies of the standard approach to solving over-constrained temporal reasoning problems.  ...  In [3] , we developed a traditional backtracking approach to solve over-constrained IA problems.  ... 
doi:10.1007/978-3-540-28633-2_16 fatcat:yr5g2n6uffbs3fyqlr3w4vwin4

Solving Overconstrained Temporal Reasoning Problems [chapter]

Matthew Beaumont, Abdul Sattar, Michael Maher, John Thornton
2001 Lecture Notes in Computer Science  
performance to constraint weighting for the over-constrained problems.  ...  In this paper, we apply local search methods to overcome the deficiencies of the standard approach to solving over-constrained temporal reasoning problems.  ...  In [3] , we developed a traditional backtracking approach to solve over-constrained IA problems.  ... 
doi:10.1007/3-540-45656-2_4 fatcat:gswghry2lba4pdz3gdo3pnd6za

Solving constrained multi-objective problems by objective space analysis

Gideon Avigad, Carlos A. Coello Coello
2008 Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08  
In this paper a new approach to solve constrained multi-objective problems by way of evolutionary multi-objective optimization is introduced.  ...  on objective space based analysis.  ...  INTRODUCTION Approaches to solve constrained multi-objective problems by Evolutionary Multi-objective Optimization (EMO) are limited.  ... 
doi:10.1145/1389095.1389239 dblp:conf/gecco/AvigadC08 fatcat:sw4xifh5ena5zp7ubweo4e3hsq

Arc Consistency for Constrained Lexicographic Preference Trees

Eisa Alanazi
2020 IEEE Access  
We show that applying a well-known constraint propagation technique known as Arc Consistency (AC) simplifies the problem and can be utilized to construct an updated version of the original LP-tree that  ...  We formally show that the naive Backtracking algorithm can be adopted to solve the problem without performing any dominance testing in case variables and their domains are ordered based on the LP-tree.  ...  HANDLING CONSTRAINTS WITH LP-TREES This section is dedicated to introducing our approach in solving the constrained LP-tree.  ... 
doi:10.1109/access.2020.2983283 fatcat:5ymtye4vmvdkzpu3tsxa4owifu

Lagrangian Decomposition Approach Based Voltage Security Constrained Unit Commitment

Ms. S. Adhitya
2017 International Journal for Research in Applied Science and Engineering Technology  
Lagrangian Decomposition Approach method which approximates a difficult problem of constrained optimization by a simpler method is proposed.  ...  A five generating unit in IEEE-14 bus network have been taken and the proposed algorithm is applied to solve it for the SCUC with voltage constraints to demonstrate the efficiency of the proposed method  ...  Lagrangian Decomposition Approach is a well-known algorithm for solving constrained optimization problem. This decomposed problem can be often solved more easily than the original problem.  ... 
doi:10.22214/ijraset.2017.2071 fatcat:z7sqgtqz2ndj7fh3dnbgg4l4ri

Expected Value and Chance Constrained Stochastic Unit Commitment Ensuring Wind Power Utilization

Chaoyue Zhao, Qianfan Wang, Jianhui Wang, Yongpei Guan
2014 IEEE Transactions on Power Systems  
This paper proposes an expected value and chance constrained stochastic optimization approach for the unit commitment problem with uncertain wind power output.  ...  Furthermore, a combined SAA framework that considers both the expected value and the chance constraints is proposed to construct statistical upper and lower bounds for the optimization problem.  ...  ACKNOWLEDGMENT The authors would like to thank the editor and four reviewers for their sincere suggestions on improving the quality of this paper.  ... 
doi:10.1109/tpwrs.2014.2319260 fatcat:lswmedd5y5anfj3e5r2dw663rq

Constrained cohort intelligence using static and dynamic penalty function approach for mechanical components design

Omkar Kulkarni, Ninad Kulkarni, Anand J. Kulkarni, Ganesh Kakandikar
2016 International Journal of Parallel, Emergent and Distributed Systems  
This paper proposes two constraint handling approaches for an emerging metaheuristic of Cohort Intelligence (CI).  ...  The approaches have been tested by solving several constrained test problems. The performance of the SCI and DCI have been compared with algorithms like GA, PSO, ABC, d-Ds.  ...  The most common approach to solve constrained optimization problems is by using a penalty functions methods.  ... 
doi:10.1080/17445760.2016.1242728 fatcat:ltzo7sctbvbztcfx7w6fncl2du

An efficient optimal planning and control framework for quadrupedal locomotion

Farbod Farshidian, Michael Neunert, Alexander W. Winkler, Gonzalo Rey, Jonas Buchli
2017 2017 IEEE International Conference on Robotics and Automation (ICRA)  
First we formulate this problem as an optimal control problem for switched systems.  ...  In this paper, we present an efficient Dynamic Programing framework for optimal planning and control of legged robots.  ...  ACKNOWLEDGEMENT This research has been supported in part by a Max-Planck ETH Center for Learning Systems Ph.D. fellowship to Farbod Farshidian and a Swiss National Science Foundation Professorship Award  ... 
doi:10.1109/icra.2017.7989016 dblp:conf/icra/FarshidianNWRB17 fatcat:nuqxxusz7zd6fcbx5dcyjjg54i

A constructive approach to solving 3-D geometric constraint systems using dependence analysis

Yan-Tao Li, Shi-Min Hu, Jia-Guang Sun
2002 Computer-Aided Design  
In this paper, we propose a new DOF-based graph constructive method to geometric constraint systems solving that can ef®ciently handle well-, over-and under-constrained systems based on the dependence  ...  In our approach, we ®rst identify all structurally redundant constraints, then we add some constraints to well constrain the system.  ...  Among them, we distinguish three major approaches for solving declarative constraint systems: the numerical approach, symbolic approach, and synthetic approach.  ... 
doi:10.1016/s0010-4485(01)00054-9 fatcat:kfdounyn4ndhbpexiaefmiwk3m

Applying Differential Evolution to Aggregate Production Planning

Shih-Chang Wang, Ming-Feng Yeh
2014 Universal Journal of Industrial and Business Management  
For alleviating the deficiency, in this paper, we propose an improved DE strategy and a constraint handling mechanism, called the winner-based constraint handling mechanism, for solving the highly constrained  ...  The experimental results show that the improved DE strategy with the winner-based constraint handling mechanism can provide particular performance for solving the APP problem than other DE strategies.  ...  The rest of the paper is organized as follows: in section 2, the proposed approach of the improved DE strategy with the winner-based constraint handling mechanism for solving the constrained APP problem  ... 
doi:10.13189/ujibm.2014.020704 fatcat:7jk47rrrbjdtpmxohv3wxzadly

The Chance-Constrained Programming for the Lot-Sizing Problem with Stochastic Demand on Parallel Machines

S. Chotayakul, V. Punyangarm
2016 International Journal of Modeling and Optimization  
The stochastic constraints are transformed into equivalent deterministic programming ones by using the chance constrained programming approach and then obtain an optimal solution by deterministic mixed-integer  ...  He has published number of research papers in the field of lot-sizing problem model based fuzzy approach in inventory planning.  ...  They proposed an exact stochastic constraint programming approach based on global chance-constraints which extends the original stochastic constraint programming model.  ... 
doi:10.7763/ijmo.2016.v6.503 fatcat:vdobmdvuh5f6xivhjx5wiyitje

Extensions of Firefly Algorithm for Nonsmooth Nonconvex Constrained Optimization Problems [chapter]

Rogério B. Francisco, M. Fernanda P. Costa, Ana Maria A. C. Rocha
2016 Lecture Notes in Computer Science  
Original FA was created and successfully applied to solve bound constrained optimization problems.  ...  In this paper we present extensions of FA for solving nonsmooth nonconvex constrained global optimization problems.  ...  Constraint-Handling Techniques In population-based methods, the widely used approach to deal with constrained optimization problems is based on exterior penalty methods [18, 19, 20, 21] .  ... 
doi:10.1007/978-3-319-42085-1_31 fatcat:vf5w3vedubcx5dmmqwq2fvqtd4

A New Approach for Low-Dimensional Constrained Engineering Design Optimization Using Design and Analysis of Simulation Experiments

Amir Parnianifard, Ratchatin Chancharoen, Gridsada Phanomchoeng, Lunchakorn Wuttisittikulkij
2020 International Journal of Computational Intelligence Systems  
This paper presents an adaptive algorithm called the Surrogate-Based Constrained Global-Optimization (SCGO) method to solve black-box constrained simulation-based optimization problems involving computationally  ...  The results demonstrate that SCGO has advantages in solving the costly constrained problems and needs less costly function evaluations.  ...  PROPOSED ALGORITHM In this section, the proposed approach namely Surrogate-Based Constrained Global-Optimization (SCGO) is described which solves the constrained optimization problem.  ... 
doi:10.2991/ijcis.d.201014.001 fatcat:pi6xj6jcmnhnpdpnnx5r7ryo2y

Constraint-handling in nature-inspired numerical optimization: Past, present and future

Efrén Mezura-Montes, Carlos A. Coello Coello
2011 Swarm and Evolutionary Computation  
In their original versions, nature-inspired search algorithms lack a mechanism to deal with the constraints of a numerical optimization problem.  ...  For each one of them, the most popular approaches are analyzed in more detail and some representative instantiations are further discussed.  ...  [131] used SR with its original search algorithm (an ES) for solving reactive power optimization problems.  ... 
doi:10.1016/j.swevo.2011.10.001 fatcat:uymwk3vfqjed5plfrdmou5zlv4
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