Mihalis M. Golias

The Berth-Scheduling Problem: Maximizing Berth Productivity and Minimizing Fuel Consumption and Emissions Production

This paper presents a new formulation for the discrete space berth-scheduling problem at marine container terminals. This formulation reflects an environmentally friendly berth-scheduling policy with the objectives of (a) maximizing berth productivity by minimizing the total service time and delayed departures for all vessels and (b) minimizing the total emissions and fuel consumption for all vessels while in transit to their next port of call. A genetic algorithms–based heuristic is presented to solve the resulting problem, and computational examples are presented to evaluate the proposed berth-scheduling policy.

Robust berth scheduling at marine container terminals via hierarchical optimization

In this paper, we present a mathematical model and a solution approach for the discrete berth scheduling problem, where vessel arrival and handling times are not known with certainty. The proposed model provides a robust berth schedule by minimizing the average and the range of the total service times required for serving all vessels at a marine container terminal. Particularly, a bi-objective optimization problem is formulated such that each of the two objective functions contains another optimization problem in its definition. A heuristic algorithm is proposed to solve the resulting robust berth scheduling problem. Simulation is utilized to evaluate the proposed berth scheduling policy as well as to compare it to three vessel service policies usually adopted in practice for scheduling under uncertainty.

Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty

This paper studies scheduling of inbound trucks at the inbound doors of a cross-dock facility under truck arrival time uncertainty. Arrival time of an inbound truck is considered to be unknown. In particular, the cross-dock operator only acknowledges the arrival time window of each truck, i.e., the lower and upper bounds of any inbound trucks arrival time. In absence of any additional information, the cross-dock operator may use three approaches to determine a scheduling strategy: deterministic approach (which assumes expected truck arrival times are equal to their mid-arrival time windows), pessimistic approach (which assumes the worst truck arrivals will be realized), and optimistic approach (which assumes the best truck arrivals will be realized). In this paper, a bi-level optimization problem is formulated for pessimistic and optimistic approaches. We discuss a Genetic Algorithm (GA) to solve the truck-to-door assignments for given truck arrival times, which solves the deterministic approach. Then the GA is modified to solve the bi-level formulations of the pessimistic and the optimistic approaches. Our numerical studies show that an hybrid approach regarding the pessimistic and the optimistic approaches may outperform all of the three approaches in certain cases.

An optimization based genetic algorithm heuristic for the berth allocation problem

Genetic algorithms have been used extensively in the studies on the Berth allocation problem (BAP). In this paper we present an optimization based genetic algorithm heuristic for the discrete and dynamic BAP that is independent of the objective function of the problem. It is evaluated by considering the problem of allocating space at a berth for vessels with the objective of minimizing the total weighted service time of all the vessels. The problem is formulated as a linear mixed integer program. Computational experiments are reported to evaluate the efficiency of the proposed heuristic.

Analysis of injury severity of large truck crashes in work zones

Work zones are critical parts of the transportation infrastructure renewal process consisting of rehabilitation of roadways, maintenance, and utility work. Given the specific nature of a work zone (complex arrangements of traffic control devices and signs, narrow lanes, duration) a number of crashes occur with varying severities involving different vehicle sizes. In this paper we attempt to investigate the causal factors contributing to injury severity of large truck crashes in work zones. Considering the discrete nature of injury severity categories, a number of comparable econometric models were developed including multinomial logit (MNL), nested logit (NL), ordered logit (ORL), and generalized ordered logit (GORL) models. The MNL and NL models belong to the class of unordered discrete choice models and do not recognize the intrinsic ordinal nature of the injury severity data. The ORL and GORL models, on the other hand, belong to the ordered response framework that was specifically developed for handling ordinal dependent variables. Past literature did not find conclusive evidence in support of either framework. This study compared these alternate modeling frameworks for analyzing injury severity of crashes involving large trucks in work zones. The model estimation was undertaken by compiling a database of crashes that (1) involved large trucks and (2) occurred in work zones in the past 10 years in Minnesota. Empirical findings indicate that the GORL model provided superior data fit as compared to all the other models. Also, elasticity analysis was undertaken to quantify the magnitude of impact of different factors on work zone safety and the results of this analysis suggest the factors that increase the risk propensity of sustaining severe crashes in a work zone include crashes in the daytime, no control of access, higher speed limits, and crashes occurring on rural principal arterials.

A Multi-Objective Decision and Analysis Approach for the Berth Scheduling Problem

Berth scheduling can be described as the resource allocation problem of berth space to vessels in a container terminal. When defining the allocation of berths to vessels container terminal operators set several objectives which ideally need to be optimized simultaneously. These multiple objectives are often non-commensurable and gaining an improvement on one objective often causes degrading performance on the other objectives. In this paper, the authors present the application of a multi-objective decision and analysis approach to the berth scheduling problem, a resource allocation problem at container terminals. The proposed approach allows the port operator to efficiently select a subset of solutions over the entire solution space of berth schedules when multiple and conflicting objectives are involved. Results from extensive computational examples using real-world data show that the proposed approach is able to construct and select efficient berth schedules, is consistent, and can be used with confidence.

Evaluation of the floaterm concept at marine container terminals via simulation

Abstract International seaborne trade rose significantly during the past decades. This created the need to increase capacity of existing marine container terminals to meet the growing demand. The major objective of this paper is to evaluate the floaterm concept using simulation modeling and determine if it can improve terminal productivity. The main difference between floaterm and conventional marine container terminals is that, in the former case, transshipment containers are handled by off-shore quay cranes and stored on container barges. Two terminal configurations performance is compared (vessel handling times and equipment utilization) under normal and disruptive conditions. Computational experiments confirm preliminary expectations that the floaterm concept can enhance efficiency of marine container terminal operations under normal and disruptive conditions.

Attracting Students to Transportation Engineering: Gender Differences and Implications of Student Perceptions of Transportation Engineering Careers

With a significant fraction of the nations transportation workforce nearing retirement age, it is essential to attract new talent to transportation fields and to retain that talent. In addition, it is also important to attract a diverse workforce, because women and minorities are still significantly under-represented in transportation engineering and related fields. To address the nations transportation workforce needs, FHWA, the U.S. Department of Transportation, the Institute of Transportation Engineers, and other leading transportation organizations emphasize the importance of outreach activities in kindergarten through 12th grade. In particular, programs directed at middle and high school students are essential for increasing the pipeline of transportation students and professionals. One such program at the University of Memphis in Tennessee, Transportation Engineering Careers (TREC), is designed to increase high school students’ interest in transportation careers through a week-long, fast-paced, active learning environment. This paper first provides a review of relevant literature and then presents assessment findings from the first 2 years of the TREC program regarding gender differences and student perceptions of transportation engineering. Finally, lessons learned and implications for similar efforts are also presented.

Scheduling of Inbound Trucks at a Cross-Docking Facility: Bi-Objective VS Bi-Level Modeling Approaches

This paper examines the problem of scheduling of inbound trucks to the inbound doors at a cross-docking facility. The authors optimize for two conflicting objectives: minimize the total service time for all the inbound trucks and minimize the delayed completion of service for a subset of the inbound trucks, which are considered as preferential customers. The problem is formulated as a bi-objective and as a bi-level mixed integer problem. Due to the nature of the former and the complexity of the latter formulation, a genetic algorithm and a k-th best based algorithm are proposed as the solution approaches. Computational examples are used to discuss the advantages and drawbacks of each formulation.

Advances in Truck Scheduling at a Cross Dock Facility

In this paper the authors deal with the scheduling of inbound and outbound trucks to the available inbound and outbound doors at a cross dock facility. They assume that all trucks served at the facility need to meet several deadlines for deliveries and pick-ups and thus request a departure time window from the facility, penalizing the facility operator, on a unit of time basis, if that deadline is not met. To solve the resulting problem with reasonable computational effort, a memetic algorithm is developed and a number of computational examples show the efficiency of the proposed solution algorithm and the advantages of scheduling inbound and outbound trucks simultaneously, as opposed to sequentially.