Showing papers by "Hiroshi Morita published in 2015"

A Column Generation Model for the Electric and Fuel-Engined Vehicle Routing Problem

Abstract: Electric vehicles have recently received attention due to the environmental and financial implication. However, they are still not popular because of their inconvenience, limited battery capacities and long recharge times. In order to grow popular of electric vehicles, several studies in the field of optimization have been engaged. One of the studies is routing problem for energy-optimized driving. In this paper, we deal with the electric and fuel-engined vehicle routing problem (EFVRP), this problem is a type of the vehicle routing problem where we use electric vehicles and fuel-engined vehicles (e.g. Gasoline-powered vehicles). We model the EFVRP and propose a column generation approach for the EFVRP. Experiments compare the results obtained using our model and algorithm with their lower bounds.

Global Optimization with Gaussian Regression Under the Finite Number of Evaluation

Abstract: Computer experiments are black-box functions that are expensive to evaluate. One solution to expensive black-box optimization is Bayesian optimization with Gaussian processes. This approach is popularly used in this challenge, and it is efficient when the number of evaluations is limited by cost and time constraints, which is generally true in practice. This paper discusses an optimization method with two acquisition functions. Our new method improves the efficiency of global optimization when the number of evaluations is strictly limited.