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HEURISTICS FOR THE DESIGN OF BI-CONNECTED TELECOMMUNATION NETWORKS
We focus on the design of telecommunication networks with minimum cost. The cost is made up of two components: distance and route. Given a fixed node distribution, several heuristics are proposed to determine the optimal ...
Solving Constraint Satisfaction Puzzles with Constraint Programming
(2009-09-17)
Constraint Programming (CP) is a powerful paradigm for solving
Combinatorial Problems (generally issued from Decision Making). In CP,
Enumeration Strategies are crucial for resolution performances. In this work,
we model ...
Distribution network planning using a constructive heuristic algorithm
(2009-12-01)
An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining ...
Distribution network planning using a constructive heuristic algorithm
(2009-12-01)
An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining ...
Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem
(Univ Nac Colombia, Fac Ingenieria, 2014)
Improving the shift-scheduling problem using non-stationary queueing models with local heuristic and genetic algorithm
(2020-01-01)
We improve the shift-scheduling process by using nonstationary queueing models to evaluate schedules and two heuristics to generate schedules. Firstly, we improved the fitness function and the initial population generation ...
A Hybrid Heuristic for the k-medoids Clustering Problem
(Assoc Computing Machinery, 2012-01-01)
Clustering is an important tool for data analysis, since it allows the exploration of datasets with no or very little prior information. Its main goal is to group a set of data based on their similarity (dissimilarity). A ...
Identifying Discrete Choice Models With Multiple Choice Heuristics
(2018)
Understanding and forecasting the behaviour of individuals is key in different realms of society such as public policy and marketing. Discrete choice models are an important econometric tool for understanding these behaviours. ...