An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
A matrix formulation for an adaptive genetic algorithm is developed using mutation matrix and crossover matrix. Selection, mutation, and crossover are all parameter-free in the se...
In this paper we consider solving a complex real life break scheduling problem. This problem of high practical relevance arises in many working areas, e.g. in air traffic control a...
The original Parameter-Less Self-Organising Map (PLSOM) algorithm was introduced as a solution to the problems the Self-Organising Map (SOM) encounters when dealing with certain ty...
In this paper, we present a stochastic version of the Location Model with Risk Pooling (LMRP) that optimizes location, inventory, and allocation decisions under random parameters ...
Lawrence V. Snyder, Mark S. Daskin, Chung-Piaw Teo