This work models Word Sense Disambiguation (WSD) problem as a Distributed Constraint Optimization Problem (DCOP). To model WSD as a DCOP, we view information from various knowledge sources as constraints. DCOP algorithms have the remarkable property to jointly maximize over a wide range of utility functions associated with these constraints. We show how utility functions can be designed for various knowledge sources.
This paper proposes a new probabilistic algorithm for solving multi-objective optimization problems - Probability-Driven Search Algorithm. The algorithm uses probabilities to control the process in search of Pareto optimal solutions. Especially, we use the absorbing Markov Chain to argue the convergence of the algorithm. Authors test this approach by implementing the algorithm on some benchmark multi-objective optimization problems, and find very good and stable results.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Optimality Conditions for Approximate Solutions in Multiobjective Optimization Problems
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known probabilistic meta-heuristic. It is used to solve discrete and continuous optimization problems. The significant advantage of SA over other solution methods has made it a practical solution method for solving complex optimization problems. Book is consisted of 13 chapters, classified in single and multiple objectives applications and it provides the reader with the knowledge of SA and several applications.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Hybrid Method for a Class of Stochastic Bi-Criteria Optimization Problems
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Some Iterative Methods for Solving Equilibrium Problems and Optimization Problems
Ant Colony Optimization (ACO) is the best example of how studies aimed at understanding and modeling the behavior of ants and other social insects can provide inspiration for the development of computational algorithms for the solution of difficult mathematical problems. Introduced by Marco Dorigo in his PhD thesis (1992) and initially applied to the travelling salesman problem, the ACO field has experienced a tremendous growth, standing today as an important nature-inspired stochastic metaheuristic for hard optimization problems....
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A General Iterative Approach to Variational Inequality Problems and Optimization Problems
Jong Soo Jung
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Strong Convergence Theorems for Countable Lipschitzian Mappings and Its Applications in Equilibrium and Optimization Problems
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A general composite iterative method for generalized mixed equilibrium problems, variational inequality problems and optimization problems
In this paper we consider a combinatorial optimization problem that is similar to the bottleneck traveling salesman problem. We show that an optimal tour for this problem is pyramidal tour (1, 3, 5,…, n,…, 6, 4, 2) or consists of some pyramidal subtours. The above 7methods can be extended to complete bipartite graphs. 1.
It is well-known that the traveling salesman problem (TSP) is strongly NP-hard (cf. , p. 353). But for some special cases of the TSP can be solvable in polynomial time. ...
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài:
Research Article Existence of Solutions for Nonconvex and Nonsmooth Vector Optimization Problems
The most common way in which probabilities are associated with combinatorial
optimization problems is to consider that the data of the problem are deterministic (always
present) and randomness carries over the relation between these data (for example,
randomness on the existence of an edge linking two vertices in the framework of
a random graph theory problem ([BOL 85]) or randomness on the fact that an element
is included to a set or not, when dealing with optimization problems on set-systems or,
even, randomness on the execution time of a task in scheduling problems).
In this concept, you will learn to find the optimal value of a function that is associated with an optimization problem. At this point, you know how to analyze a function to find its minima and maxima using the first and second derivatives. This is a big deal! Finding the solution to some real-world problem (such as in finance, science, and engineering) often involves a process of finding the maximum or minimum of a function within an acceptable region of values.
I have been undertaking the research and practical applications of power
system optimization since the early 1980s. In the early stage of my career, I
worked in universities such as Chongqing University (China), Brunel
University (UK), National University of Singapore, and Howard University
(USA). Since 2000 I have been working for AREVA T & D Inc (USA). When
I was a full - time professor at Chongqing University, I wrote a tutorial on power
system optimal operation, which I used to teach my senior undergraduate
students and postgraduate students in power engineering until 1996.
Problem statement: Dilute sulphuric acid and enzymatic hydrolysis methods were used for sugar extraction. Xylose and glucose sugars were obtained from corn cobs. Approach: Acid hydrolysis of corn cobs gave higher amount of sugars than enzymatic hydrolysis. Results: The results showed that optimal temperature and time for sugar fermentation were approximately 25°C and 50 h by two yeast strains (S. cerevisiae and P. Stipitis) respectively.
Parametric representation of shapes, mechanical components modeling with 3D visualization techniques using object oriented programming, the well known golden ratio application on vertical and horizontal displacement investigations of the ground surface, spatial modeling and simulating of dynamic continuous fluid flow process, simulation model for waste-water treatment, an interaction of tilt and illumination conditions at flight simulation and errors in taxiing performance, plant layout optimal plot plan, atmospheric modeling for weather prediction, a stochastic search method that explores ...
Pre-launch optimization basically deals withassessing a newly-built network, uncoveringproblems and resolving them prior to commerciallaunch. It entails detailed field rf measurements,detecting and rectifying problems caused byradio, improper parameter settings or networkfaults and finally, grading the radio access part of the network to make sure that it passes certainevaluation criteria