Catálogo de publicaciones - libros

In automated container terminals, situations occur where quay cranes, stacking cranes, and automated guided vehicles (AGVs), directly or indirectly request each other to start a specific process. Hence, all of the affected resources are blocked, possibly leading to the complete deadlock of individual cranes or AGVs. Particularly, AGVs are liable to deadlocks because they always need a secondary resource, either a quay crane or a stacking crane, to perform the pick-up and drop-off operations. Because usually no buffering of containers takes place at the interfaces between AGVs and cranes, the consequences of deadlocks are rather severe. Two different methods for the detection of deadlocks are presented. One is based on a matrix representation of the terminal system. The other directly traces the requests for the individual resources. To resolve deadlock situations arising in an automated container terminal, three different procedures are proposed. These procedures aim to modify the sequence of handling operations or to assign them to alternative resources so that conflicts between concurrent processes are resolved. The suitability of the concept is demonstrated in an extensive simulation study.

Automated guided vehicles (AGVs) are an important component for automating container terminals. When utilizing AGVs to transport containers from one position to another in a container terminal, deadlocks are a serious problem that must be solved before real operations can take place. This study assumes that the traveling area for AGVs is divided into a large number of grid-blocks, and, as a method of traffic control, grid-blocks are reserved in advance when AGVs are running. The first purpose of the reservation is to make room between AGVs and to prevent deadlocks. The objective of this study is to develop an efficient deadlock prediction and prevention algorithm for AGV systems in automated container terminals. Because the size of an AGV is much larger than the size of a grid-block on a guide path, this study assumes that an AGV may occupy more than one grid-block at a time. This study proposes a method for reserving grid-blocks in advance to prevent deadlocks. A graphical representation method is suggested for a reservation schedule and a priority table is suggested to maintain priority consistency among grid-blocks. It is shown that the priority consistency guarantees deadlock-free reservation schedules for AGVs to cross the same area at the same time. The proposed method was tested in a simulation study.

We address the planning of transportation and storage capacity over time. In intermodal transshipment terminals, finished vehicles are assigned to yard locations for intermediate storage. The evolutionary algorithm proposed evolves a period-oriented capacity utilization strategy. This capacity utilization strategy then controls a construction heuristic which assigns vehicle movements to periods and vehicles to storage locations. It is aimed at efficient operations and at a balanced distribution of vehicle movements over the periods of the planning horizon.

We consider a large air cargo handling facility composed of two identical cargo terminals. In order to improve the operational efficiency, the workload must be balanced between the terminals. Thus, we must assign each airline served by the facility to one of the terminals such that (ideally): (1) each terminal has the same total workload, and (2) the workload at each terminal is distributed evenly along the timeline. Complicating the problem is that cargo loads are difficult to predict (stochastic). We develop a stochastic mixed integer linear program model in which a weighted sum of the balance measures is minimized. We employ sample average approximation for the stochastic program and develop an accelerated Benders decomposition algorithm to reduce the computational time. The proposed model can also be applied to partially reassign the airlines for the operational schedule changes. The computational results show that a small number of reassignments are often sufficient to rebalance the workload. The simulation results based on data from a large international airport show that the proposed algorithms efficiently balance the workload and the cargo service time is consistently reduced.

In this paper, we incorporate the cargo routing problem into fleet assignment to model the fleet assignment more accurately. An integrated model and a Benders decomposition-based approach are developed to simultaneously obtain the optimal assignment of fleet to legs and the routing of forecasted cargo demand over the network. Computational experiments show that this integrated approach converges very fast for all different test scenarios.

In this paper we present a mathematical programming based approach for revenue management in cargo airlines. The approach is based on a modified version of a multicommodity network flow model which has been developed in a decision support approach for schedule planning in cargo airlines. We think that using the same concept for planning and revenue management is essential for consistency of planning and operation. To meet the real-time requirements of revenue management special computational strategies for solving the large models are necessary.

In this paper, we will introduce a heuristic to solve a single leg revenue management problem with postponement, arising from the sea cargo industry. Based on previous work, it was shown that the optimal policy to allocate the capacity of the ship is a threshold policy. Based on the sample average approximation method, we formulate a mixed integer linear programming problem to determine the stationary threshold policy. A heuristic (known as the perturbation approach) is proposed to solve the problem. From the numerical result, it is shown that our approach performs better than some of the methods used to solve the mixed-integer programming problem.

The paper presents a model for the collaboration among independent freight forwarding entities. In the modern highly competitive transportation branch freight forwarders reduce their fulfillment costs by exploiting different execution modes (self-fulfillment and subcontraction). For self-fulfillment they use their own vehicles to execute the requests and for subcontracting they forward the orders to external freight carriers. Further enhancement of competitiveness can be achieved if the freight forwarders cooperate in coalitions in order to balance their request portfolios. Participation in such a coalition gains additional profit for the entire coalition and for each participant, therefore reinforcing the market position of the partners. The integrated operational transport problem as well as existing collaboration approaches are introduced. The presented model for collaboration is based on theoretical foundations in the field of combinatorial auctions and operational research game theory. It is applicable for coalitions of freight forwarders, especially for the collaboration of Profit Centres within large freight forwarding companies. The proposed theoretical approach and the presented collaboration model are suitable for a coalition of freight forwarding companies with nearly similar potential on the market.