A Simulation Based Approach to Optimize Berth Throughput Under Uncertainty at Marine Container Terminals

Berth scheduling is a critical function at marine container terminals and determining the best berth schedule depends on several factors including the type and function of the port, size of the port, location, nearby competition, and type of contractual agreement between the terminal and the carriers. In this paper we formulate the berth scheduling problem as a bi-objective mixed-integer problem with the objective to maximize customer satisfaction and reliability of the berth schedule under the assumption that vessel handling times are stochastic parameters following a discrete and known probability distribution. A combination of an exact algorithm, a Genetic Algorithms based heuristic and a simulation post-Pareto analysis is proposed as the solution approach to the resulting problem. Based on a number of experiments it is concluded that the proposed berth scheduling policy outperforms the berth scheduling policy where reliability is not considered

Loading Time Flexibility in Cross-Docking Systems

In this study, we investigate truck-to-door assignment problem for loading outgoing trucks in a cross-docking system with flexible handling times. Specifically, a truck\u27s loading time depends on the number of workers assigned to the outbound door, where the truck is being loaded. An optimization problem is formulated to jointly determine the number of workers and the trucks to be loaded at each door. The resulting problem is a nonlinear integer programming model. Due to the complexity of this model, two evolutionary heuristic methods are proposed for solution. First heuristic method is based on truck assignments while the second heuristic is based on worker assignments. A numerical study is conducted to compare the two heuristic methods

Towards Sustainable Tourism Transportation Systems and Services in Tennessee

RES2021-02Tennessee is home to some of the most popular tourist destinations in the country and the tourism industry contributes considerably to Tennessee\u2019s economy. The industry in the state has grown considerably in the previous years and there is a need to identify and address issues related to transportation services to accommodate needs and requirements of tourists. This study identifies current deficiencies in the transportation system dedicated to tourists, and popular tourist destinations and origin markets. The findings from the study are used to provide policy level recommendations for improving tourism focused transportation system in the state. Results show that continued involvement of local and private tourism agencies in transportation project planning is needed, and the collaboration between the state DOT, state tourism office and tourism agencies should be encouraged for a tourism focused transportation system. Analysis of origin markets for major destinations show that most travels to Tennessee are attracted from bordering states. This can help agencies identify routes of interest for future improvement and expansion. Finally, based on our findings, key policy recommendations are presented to improve the current state of transportation system and services for tourism in the state

A bi-objective berth allocation formulation to account for vessel handling time uncertainty

In this article we formulate the berth allocation problem as a bi-objective mixed-integer programming problem with the objective to maximize berth throughput and reliability of the schedule under the assumption that vessel handling times are stochastic parameters, being a function of other stochastic parameters (that is, quay crane breakdowns, quay-to-yard transport vehicle productivity, yard congestion, and so on). A combination of an exact algorithm, a Genetic Algorithms-based heuristic and a Monte Carlo simulation are proposed as the solution approach for the resulting problem. Based on a number of simulation experiments, it is shown that the proposed modeling approach is effective and outperforms berth allocation solutions where reliability is not considered.

Topological-based measures with flow attributes to identify critical links in a transportation network

An important part of transportation network vulnerability analysis is identifying critical links where failure may lead to severe consequences, and the potential of such incidents cannot be considered negligible. Existing transportation network vulnerability assessment can be categorized as topological, or traffic based. Topological-based assessment identifies the most critical components in the network by considering network structure and connectivity. Traffic-based assessment identifies the most critical components in the network by full-scan analysis and takes into consideration effects of link failures to traffic flow assignment. The former approach does not consider traffic flow dynamics and fails to capture the non-linearity performance function of transport systems while the latter, even though accurate and robust, requires significant computational power and time and may not always be feasible for real life size networks. The primary objective of this paper is to propose new link criticality measures and evaluate their accuracy for transportation network vulnerability assessment. These measures combine characteristics of traffic equilibrium and network topology to balance accuracy and computational complexity. Nine measures are proposed, and their accuracy is compared with three existing traffic-based measures using three case study transportation networks from the literature. Results indicate that three of the proposed measures show strong correlation to the three traffic-based measures while requiring significantly less computational power and time

The berth allocation problem: a formulation reflecting time Window service deadlines

The berth-allocation problem (BAP) aims to optimally schedule and assign vessels to berthing areas along a quay. The vessels arrive at the port over a period of time and normally request service and departure within a time window. These time windows are usually determined through contractual agreements between the port operator and the carrier, in terms of time of departure after the vessel’s arrival at the port. Formulations presented in the current literature, reduce the time window to a point in time. In this paper the discrete dynamic BAP (DDBAP) is formulated as a linear MIP problem with the objective to simultaneously minimize the cost from vessels’ late departures (departure past the time window) and maximize the benefits from vessels’ early departures and timely departures (departure before and within the requested time window). Two different models along with numerical examples and a comparison to other BAP models are presented to demonstrate the benefits of the proposed berth scheduling formulation