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AAAI
2000
13 years 9 months ago
Solving a Supply Chain Optimization Problem Collaboratively
We propose a novel algorithmic framework to solve an integrated planning and scheduling problem in supply chain management. This problem involves the integration of an inventory m...
Hoong Chuin Lau, Andrew Lim, Qi Zhang Liu
ICML
2000
IEEE
14 years 8 months ago
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Jun Wang, Jean-Daniel Zucker
ICNC
2009
Springer
14 years 2 months ago
An Improved Greedy Genetic Algorithm for Solving Travelling Salesman Problem
—Genetic algorithm (GA) is too dependent on the initial population and a lack of local search ability. In this paper, an improved greedy genetic algorithm (IGAA) is proposed to o...
Zhenchao Wang, Haibin Duan, Xiangyin Zhang
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
14 years 1 months ago
Transition models as an incremental approach for problem solving in evolutionary algorithms
This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model in which parti...
Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, J...
GECCO
2000
Springer
225views Optimization» more  GECCO 2000»
13 years 11 months ago
Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm
A genetic local search (GLS) algorithm, which is a combination technique of genetic algorithm and local search, for the unconstrained binary quadratic programming problem (BQP) is...
Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa