Distributed approach for optimization problems
نویسندگان
چکیده
منابع مشابه
Solving Combinatorial Optimization Problems using Distributed Approach
Combinatorial optimization is a way of finding an optimum solution from a finite set of objects. For combinatorial optimization problems, the number of possible solutions grows exponentially with the number of objects. These problems belong to the class of NP hard problems for which probably efficient algorithm does not exist. Using the distributed approach with parallelization these problems c...
متن کاملA Distributed Reinforcement Learning Approach for Solving Optimization Problems
Combinatorial optimization is the seeking for one or more optimal solutions in a well defined discrete problem space. The optimization methods are of great importance in practice, particularly in the engineering design process, the scientific experiments and the business decision-making. We are investigating in this paper a distributed reinforcement learning based approach for solving combinato...
متن کاملPartitioning Problems for Distributed Optimization
The Alternating Directions Method of Multipliers (ADMM) ([BPC+11]) paradigm for distributed optimization assumes that the objective of an optimization problem splits into two additive components which are separately easy to optimize. Here, I generalize the ADMM paradigm to problems with an arbitrary number of additive components in the objective, and ask the question: how can we partition the o...
متن کاملUtilitarian Approach to Privacy in Distributed Constraint Optimization Problems
Privacy has been a major motivation for distributed problem optimization. However, even though several methods have been proposed to evaluate it, none of them is widely used. The Distributed Constraint Optimization Problem (DCOP) is a fundamental model used to approach various families of distributed problems. Here we approach the problem by letting both the optimized costs found in DCOPs and t...
متن کاملFully Distributed Algorithms for Convex Optimization Problems
We design and analyze a fully distributed algorithm for convex constrained optimization in networks without any consistent naming infrastructure. The algorithm produces an approximately feasible and near-optimal solution in time polynomial in the network size, the inverse of the permitted error, and a measure of curvature variation in the dual optimization problem. It blends, in a novel way, go...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IOP Conference Series: Materials Science and Engineering
سال: 2020
ISSN: 1757-899X
DOI: 10.1088/1757-899x/734/1/012145