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Showing 1 to 20 of 71 for “"Combinatorial Optimization Problems"”.
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Probabilistic combinatorial optimization problems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1988.
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Combinatorial optimization problems with concave costs
… and linear in 1/c. For several concave cost problems, the resulting piecewise linear problem can be reformulated as a classical combinatorial optimization problem. As a result of our bound, a variety of polynomial-time heuristics, approximation algorithms, and exact algorithms for classical …
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Proxy-Based Acceleration for Combinatorial Optimization Problems
Combinatorial optimization problems occur in a wide range of domains, from Bayesian network structure search to questions in neuroscience and biochemistry. However, all of these problems have in common the need to optimize some score, and often the calculation of this score is a significant source …
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Polyhedral aspects of cardinality constrained combinatorial optimization problems
… kombinatorische Strukturen eines gegebenen Problems einbinden. Auf diese Weise gelingt es uns, für verschiedene kardinalitätsbeschränkte Probleme facettendefinierende Ungleichungen herzuleiten, insbesondere für die oben namentlich genannten Polytope. Außerdem präsentieren wir weitere Klassen …
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A Differential Evolution Algorithm for Generic Combinatorial Optimization Problems
Combinatorial optimization problems (COPs) are well-known NP-hard realistic ones. Due to the drawbacks of existing approaches, many researchers proposed different evolutionary algorithms (EAs) for solving them. Differential evolution (DE) is primarily used to solve continuous-based optimization …
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Learning Heuristics for Combinatorial Optimization Problems with Deep Neural Networks
Solving real-world combinatorial optimization problems with traditional operations research methods can be a costly and time-consuming endeavor, often requiring the development of completely new methods or significant modification of exist- ing techniques. This has led many organizations to forego …
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Multi-objective combinatorial optimization problems in transportation and defense systems
"Multi-objective Optimization problems arise in many applications; hence, solving them efficiently is important for decision makers. A common procedure to solve such problems is to generate the exact set of Pareto efficient solutions. However, if the problem is combinatorial, generating the exact …
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Cyclic exchange and related neighborhood structures for combinatorial optimization problems
… search based approach for partitioning problems. A partitioning problem is to divide a set of n elements into K subsets S1,... ,SK so as to minimize f(S1)+...+f(SK) for some specified function f. A partition S'1,.. ,S'K is called a cyclic exchange neighbor of the partition S1,...,SK if …
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Two Combinatorial Optimization Problems at the Interface of Computer Science and Operations Research
… this dissertation also proposes a new discrete optimization problem to help the decision-maker to obtain an optimal preferred subset of Pareto optimal solutions. This discrete optimization problem is proven to be NP-hard. To solve this problem, exact algorithms and heuristic methods are …
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Entropy-based framework for combinatorial optimization problems and enabling the grid of the future
… meta-heuristic algorithms for a series of combinatorially complex optimization problems, while the second part is concerned with robust and scalable control architecture for a network of paralleled converter/inverter systems (DC/AC microgrids). Combinatorial optimization problems arise in …
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The polyhedral structure of certain combinatorial optimization problems with application to a naval defense problem
… of the polyhedral structure of three important combinatorial optimization problems, namely, the generalized upper bounding (GUS) constrained knapsack problem, the set partitioning problem, and the quadratic zero-one programming problem, and applies related techniques to solve a practical …
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A proposal for an improved version of EigenAnt algorithm with performance evaluation on combinatorial optimization problems
… algorithm applied to N-node Binary Chain Problems is carried out. Motivated by this analysis, an improved EigenAnt algorithm is proposed, in which the exploration of different stable equilibria and speed of convergence to them can be tuned separately. A comparative analysis of Improved …
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Models and Algorithms for Some Combinatorial Optimization Problems: University Course Timetabling, Facility Layout and Integrated Production-Distribution Scheduling
In this dissertation, we address three different combinatorial optimization problems (COPs), each of which has specific real-life applications. Owning to their specific nature, these problems are different from those discussed in the literature. For each of these problems, we present a mathematical …
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Topics in Combinatorial Algorithms (Multicommodity Flows, Quadratic Programming)
This thesis is a study of a wide variety of combinatorial optimization problems.
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Attention-Based Learning for Combinatorial Optimization
Combinatorial optimization problems, such as the Traveling Salesman Problem (TSP), have been studied for decades. However, with the rise of reinforcement learning in recent years, many of these problems are being revisited as a way to gauge these new models in different environments. In this …
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Approximation algorithms for combinatorial optimization under uncertainty
Combinatorial optimization problems arise in many fields of industry and technology, where they are frequently used in production planning, transportation, and communication network design. Whereas in the context of classical discrete optimization it is usually assumed that the problem inputs are …
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Modification of the simulated annealing optimization technique and its application to both a dynamic control and gas tagging problem
Advanced optimization techniques, based on analogies related to physical systems rather than on classical mathematical theory, are becoming more widely used than ever before. One such type of technique is simulated annealing, a Monte Carlo (stochastic) method. Although it has been used primarily …
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Modelo de computación evolutivo para redes sostenibles, eficientes y resistentes.
… (DE) algorithm so that it can be applied in combinatorial optimization problems. The differential evolution algorithm has been proposed as an optimization algorithm for the continuous domain, using real numbers to encode the solutions, and its main operator, the mutation, uses a arithmetic …
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