Combinatorial Optimization Problems
Adaptive Quantum Inspired Genetic Algorithm for Combinatorial Optimization Problems
... NP-hard problems such as graph layout ...world problems are effectively solved by genetic algorithm (GA) and the performance of GA highly depends upon the setting of its parameters, therefore this paper ...
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Grammatical evolution hyper heuristic for combinatorial optimization problems
... of problems is a challenging ...known combinatorial optimization problems; exam timetabling (Carter and ITC 2007 instances) and the capacitated vehicle routing problem (Christofides and Golden ...
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A dynamic multiarmed bandit gene expression programming hyper heuristic for combinatorial optimization problems
... different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed ...
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Representative scenario construction and preprocessing for robust combinatorial optimization problems
... robust combinatorial problems are usually NP-hard, approximation methods have been considered ...of problems. While this guarantee has been improved for specific problems, they are still the ...
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Minmax regret combinatorial optimization problems with ellipsoidal uncertainty sets
... uncertain combinatorial optimiza- tion problems, where the difference to the best possible solution over all scenarios is to be ...regret problems are typically harder to solve than their nominal, ...
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Metaheuristics and combinatorial optimization problems
... of combinatorial optimization and meta- heuristics along with the abilities to solve ever larger problem ...modern problems are computationally intractable, needing heuristic guidance to find good ...
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Statistical mechanics of neural networks and combinatorial optimization problems
... */ #include #include "replica.h" void synchronous_dynamicsnetwork_ptr, temperature net *network_ptr; double temperature; int i, j; double transition_probability, local_field; net netwo[r] ...
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On scenario aggregation to approximate robust combinatorial optimization problems
... The midpoint method is a central approximation algorithm in robust optimization. De- spite its simplicity, it has been the best-known method for several classic combinatorial problems. In this paper, ...
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The automatic design of hyper heuristic framework with gene expression programming for combinatorial optimization problems
... The vehicle routing problem is a well-known challenging combinatorial optimization problem [45]. Given a set of customers associated with demand and serving time, and a fleet of vehicles with a maximum ...
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Bi objective branch and cut algorithms based on LP relaxation and bound sets
... objective combinatorial optimization problems (see ...the optimization problem is partitioned into disjoint subproblems which can be displayed in a tree–structure where each node represents a ...
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Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization
... an optimization algorithm which produces a ...with optimization is a difficult and error-prone process (which is often skipped ...on combinatorial optimization problems and in- troduce ...
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Local Search Approximation Algorithms for Clustering Problems
... a combinatorial optimization problem we look for a that either maximizes or mini- mizes a given objective ...a combinatorial optimization problem is discrete or ...of combinatorial ...
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A novel solution to traveling salesman problem using fuzzy sets, gravitational search algorithm, and genetic algorithm
... The TSP is a representative of a large class of problems known as the combinatorial optimization problems. Among them, TSP is one of the most important, since it is very easy to describe, but ...
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On Metaheuristic Optimization Motivated by the Immune System
... Extremal optimization is quite similar to the way the immune system (IS) renews its cells ...extremal optimization to solve some single objective combinatorial optimization ...
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AN IOT BASED FRAMEWORK FOR STUDENTS INTERACTION AND PLAGIARISM DETECTION IN PROGRAMMING ASSIGNMENTS
... In conventional GAs, repair and penalization procedures are widely used to deal with infeasible solutions. However, they are not included within the framework of SGA. Thus, FSWGA is easier to implement than GAs with ...
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Dictionary based super resolution for positron emission tomography images
... Rodríguez Hernández and Ochoa Domínguez / International Journal of Combinatorial Optimization Problems and Informatics, 111 2020, 9-25... Output the optimized image Fig.[r] ...
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A Continuous Approach to Binary Quadratic Problems
... of combinatorial optimization problem effectively has been the focus of many ...programming problems are mainly divided into two types: accurate algorithms and random search ...the ...
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A Lagrangian Relaxation-based Algorithm to Solve a Home Health Care Routing Problem
... This paper employs a Lagrangian relaxation-based algorithm as a type of sub-gradient algorithm to solve the combinatorial optimization problems [15]. The proposed methodology involves two main ...
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Solving Quadratic Assignment Problem Using Water Cycle Optimization Algorithm
... of combinatorial optimization problems which devote some facilities to some ...NP-hard optimization problems ...Cycle Optimization Algorithms (WCO) is used to solve ...
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Meta Heuristics approach for a Class of supply chain optimization problems D.Sabareswari, N.Sathya, K.Sharmila Abstract PDF IJIRMET160207006
... of combinatorial optimization are characterized by their well-structured problem definition as well as by their huge number of action alternatives in practical application areas of reasonable ...of ...
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