The Berth-Scheduling Problem-Reference-Cited by-同舟云学术

The Berth-Scheduling Problem

Published:2010-01 Issue:1 Volume:2166 Page:20-27
ISSN:0361-1981
Container-title:Transportation Research Record: Journal of the Transportation Research Board
language:en
Short-container-title:Transportation Research Record

Author:

Golias Mihalis¹,Boile Maria²³,Theofanis Sotiris³,Efstathiou Christos⁴

Affiliation:

1. Department of Civil Engineering, University of Memphis, 3815 Central Avenue, Memphis, TN 38152, and Freight and Maritime Program, Center for Advanced Infrastructure and Transportation, Rutgers University, 100 Brett Road, Piscataway, NJ 08854.

2. Department of Civil and Environmental Engineering, 100 Brett Road, Piscataway, NJ 08854.

3. Freight and Maritime Program, Center for Advanced Infrastructure and Transportation, Rutgers University, 100 Brett Road, Piscataway, NJ 08854.

4. Computational Chemodynamics Laboratory, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, 170 Frelinghuysen Road, Piscataway, NJ 08854.

Abstract

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.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Link

http://journals.sagepub.com/doi/pdf/10.3141/2166-03

Reference25 articles.

1. Container Terminal Berth Planning

2. A survey of berth allocation and quay crane scheduling problems in container terminals

3. Efficient planning of berth allocation for container terminals in Asia

4. The dynamic berth allocation problem for a container port

5. Berth allocation planning in the public berth system by genetic algorithms

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