This paper studies an evolutionary algorithm to solve a new multiobjective optimization problem, the Pickup and Delivery Problem with Time Windows and Demands (PDPTW-D), which extends PDP and PDP-TW. With respect to multiple optimization objectives, PDP-TW-D is to find a set of Pareto-optimal routes for a fleet of vehicles in order to serve given transportation requests. The proposed algorithm ...

This paper presents a systematic approach of optimal design and control of a surface-mount, permanent-magnet synchronous torque motor for the next-generation machine tools. A step-by-step procedure of optimization integrates multiple performance objectives and constraints to help the designer make the best decision on the final motor geometry from both design and control perspectives. In the pe...

This paper presents a successful application of simulationbased multi-objective optimization of a complex real-world scheduling problem. Concepts of the implemented simulation-based optimization architecture are described, as well as how different components of the architecture are implemented. Multiple objectives are handled in the optimization process by considering the decision makers’ prefe...

In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS)....

in this article, multiple-product pvrp with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. a mathematical formulation was provided for this problem. each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. to solve the problem, two meta-heuristic methods...