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Planning activities in a network of logistic platforms with shared resources

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Planning activities in a network of logistic platforms with shared resources. / Dell'Olmo, Paolo; Lulli, Guglielmo.
In: Annals of Operations Research, Vol. 129, No. 1, 07.2004, p. 155-169.

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Dell'Olmo P, Lulli G. Planning activities in a network of logistic platforms with shared resources. Annals of Operations Research. 2004 Jul;129(1):155-169. doi: 10.1023/B:ANOR.0000030686.79587.60

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Dell'Olmo, Paolo ; Lulli, Guglielmo. / Planning activities in a network of logistic platforms with shared resources. In: Annals of Operations Research. 2004 ; Vol. 129, No. 1. pp. 155-169.

Bibtex

@article{26210b323e0049e198e3e9feec15efc3,
title = "Planning activities in a network of logistic platforms with shared resources",
abstract = "This paper has been motivated by the study of a real application, the transshipment container terminal of Gioia Tauro in Italy. The activities in a container terminal concern with the movement of containers from/to mother vessels and feeders and with the handling and storage of containers in the yard. For such type of applications both operational (e.g., scheduling) and tactical (e.g., planning) models, currently available in the literature, are not useful in terms of operations management and resources optimization. Indeed, the former models are too detailed for the complexity of the systems, while the latter are not able to capture the operational constraints in representing those activities which limit the nominal capacity. Herein, the container terminal, or more in general a service or production system, is represented as a network of complex substructures or platforms. The idea is to formalize the concept of platform capacity, which is used to represent the operational aspects of the container terminal in a mathematical model for the tactical planning. The problem, which consists in finding an allocation of resources in each platform in order to minimize the total delay on the overall network and on the time horizon, is modelled by a mathematical programming formulation for which we carry out a computational analysis using CPLEX-MIP solver. Moreover, we present a dynamic programming based heuristic to solve larger instances in short computational time. On all but one of the smaller instances, the heuristic solutions are also optimal. On the larger instances, the maximum gap, i.e. the percentage deviation, between the heuristic solutions and the best solutions computed by CPLEX-MIP within the time limit of 3600 s, has been 6.3%.",
keywords = "Dynamic programming heuristic, Operational capacity, Planning model, Resources allocation",
author = "Paolo Dell'Olmo and Guglielmo Lulli",
year = "2004",
month = jul,
doi = "10.1023/B:ANOR.0000030686.79587.60",
language = "English",
volume = "129",
pages = "155--169",
journal = "Annals of Operations Research",
issn = "0254-5330",
publisher = "Springer",
number = "1",

}

RIS

TY - JOUR

T1 - Planning activities in a network of logistic platforms with shared resources

AU - Dell'Olmo, Paolo

AU - Lulli, Guglielmo

PY - 2004/7

Y1 - 2004/7

N2 - This paper has been motivated by the study of a real application, the transshipment container terminal of Gioia Tauro in Italy. The activities in a container terminal concern with the movement of containers from/to mother vessels and feeders and with the handling and storage of containers in the yard. For such type of applications both operational (e.g., scheduling) and tactical (e.g., planning) models, currently available in the literature, are not useful in terms of operations management and resources optimization. Indeed, the former models are too detailed for the complexity of the systems, while the latter are not able to capture the operational constraints in representing those activities which limit the nominal capacity. Herein, the container terminal, or more in general a service or production system, is represented as a network of complex substructures or platforms. The idea is to formalize the concept of platform capacity, which is used to represent the operational aspects of the container terminal in a mathematical model for the tactical planning. The problem, which consists in finding an allocation of resources in each platform in order to minimize the total delay on the overall network and on the time horizon, is modelled by a mathematical programming formulation for which we carry out a computational analysis using CPLEX-MIP solver. Moreover, we present a dynamic programming based heuristic to solve larger instances in short computational time. On all but one of the smaller instances, the heuristic solutions are also optimal. On the larger instances, the maximum gap, i.e. the percentage deviation, between the heuristic solutions and the best solutions computed by CPLEX-MIP within the time limit of 3600 s, has been 6.3%.

AB - This paper has been motivated by the study of a real application, the transshipment container terminal of Gioia Tauro in Italy. The activities in a container terminal concern with the movement of containers from/to mother vessels and feeders and with the handling and storage of containers in the yard. For such type of applications both operational (e.g., scheduling) and tactical (e.g., planning) models, currently available in the literature, are not useful in terms of operations management and resources optimization. Indeed, the former models are too detailed for the complexity of the systems, while the latter are not able to capture the operational constraints in representing those activities which limit the nominal capacity. Herein, the container terminal, or more in general a service or production system, is represented as a network of complex substructures or platforms. The idea is to formalize the concept of platform capacity, which is used to represent the operational aspects of the container terminal in a mathematical model for the tactical planning. The problem, which consists in finding an allocation of resources in each platform in order to minimize the total delay on the overall network and on the time horizon, is modelled by a mathematical programming formulation for which we carry out a computational analysis using CPLEX-MIP solver. Moreover, we present a dynamic programming based heuristic to solve larger instances in short computational time. On all but one of the smaller instances, the heuristic solutions are also optimal. On the larger instances, the maximum gap, i.e. the percentage deviation, between the heuristic solutions and the best solutions computed by CPLEX-MIP within the time limit of 3600 s, has been 6.3%.

KW - Dynamic programming heuristic

KW - Operational capacity

KW - Planning model

KW - Resources allocation

U2 - 10.1023/B:ANOR.0000030686.79587.60

DO - 10.1023/B:ANOR.0000030686.79587.60

M3 - Journal article

AN - SCOPUS:3042831252

VL - 129

SP - 155

EP - 169

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

IS - 1

ER -