Solving Real-Life Problems: Future Mobile Technology Sophistication

Solving Real-Life Time-Tabling Problems

We will compare the performance of a Genetic Algorithm and Simulated Annealing on instances of difficult real-life Time-Tabling Problems. We will further explain how the performance can be increased significantly by applying a general and very effective genotype-to-phenotype decoding. Furthermore, we will contrast the performance of Lamarckian Learning to the performance of Baldwin Learning. Fi...

Solving Real-Life Locomotive-Scheduling Problems

The locomotive scheduling problem (or the locomotive assignment problem) is to assign a consist (a set of locomotives) to each train in a pre-planned train schedule so as to provide them sufficient power to pull them from their origins to their destinations. Locomotive scheduling problems are among the most important problems in railroad scheduling. In this paper, we report the results of a stu...

Study of Complex Problem-solving in Real Life Problems

Free-Floating Bike Sharing: Solving Real-life Large-scale Static Rebalancing Problems Free-Floating Bike Sharing: Solving Real-life Large-scale Static Rebalancing Problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to stationbased bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFB...

Solving group technology problems via clique partitioning

This paper presents a new clique partitioning (CP) model for the Group Technology (GT) problem. The new model, based on a novel 0/1 quadratic programming formulation, addresses multiple objectives in GT problems by drawing on production relationships to assign differing weights to machine/ part pairs. The use of this model, which is readily solved by a basic tabu search heuristic, is illustrate...