In this paper, we address workflow management system for automatically operating yard management system which can fill up a gap between transportation and warehouse management system in supply chain management. But, it is difficult to find an optimal solution for yard operation problems because of its dynamic complexities. Instead, we propose workflow management system which describes the autom...

This paper discusses a case study of the board game of Scotland Yard from a computational perspective. Interestingly, Scotland Yard is a genuine “playgame” with imperfect information. For reasons not completely clear to me, games with imperfect information have escaped the interest of researchers in Algorithmic combinatorial gametheory. I show by means of a powerset argument, that Scotland Yard...

This reasearch studies ACO algorithms for the switch engine scheduling in a Railroad Yard. The cars are moved individually or grouped into blocks by a set of locomotives called switch engines which are dedicated to moving around the cars in the yard. The need for moving comes from the fact that the arriving trains are disassembled into blocks of cars, undergo some operations like, loading , unl...

Planning the operational procedures in a railway marshalling yard is a complex problem. When a train arrives at a marshalling yard, it is uncoupled on an arrival yard and then its cars are rolled to a classification yard. All cars should eventually be rolled to the classification track that has been assigned to the train they're supposed to depart with. However, there is normally not enough cap...

The average American generates approximately 4.5 pounds of garbage per day, for a total of 196 million tons of trash per year, most of which ends up in landfills (Shortridge, 1993). Various government and private programs have been organized to divert part of this garbage (metals, plastics, paper and cardboard, and yard and food wastes) from landfills by recycling. Yard and food wastes often ar...

In this paper, a method integrating Q-learning algorithm and simulation technique is proposed to optimize the operation scheduling in container terminals. Firstly Q-learning algorithms for yard cranes and yard trailers are designed to obtain the optimal scheduling strategy of yard cranes and yard trailers. Then Q-learning is combined with simulation to develop an integrating scheduling model in...