An almost robust optimization model for integrated berth allocation and quay crane assignment problem

Xiang, Xincheng; Liu, Changchun

doi:10.1016/j.omega.2021.102455

Cited by 40 publications

(20 citation statements)

References 63 publications

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“…Among possible approaches (i.e., Fuzzy, stochastic, etc. ), the robust optimization approach is enlisted since it can manage the uncertainty in our problem per the availability of historical data internal [68] . Moreover, when data are uncertain, robustness introduced by Bertsimas and Sim [69] may control the level of conservatism in finding optimal solutions.…”

Section: Solution Methodologymentioning

confidence: 99%

A resilient, robust transformation of healthcare systems to cope with COVID-19 through alternative resources

Ardakani

Larimi

Nejad

et al. 2023

Omega

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Section: Solution Methodologymentioning

confidence: 99%

A resilient, robust transformation of healthcare systems to cope with COVID-19 through alternative resources

Ardakani

Larimi

Nejad

et al. 2023

Omega

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“…In [21], there was a combined problem of QCAP and BAP. The aim was to obtain the best berthing positions, time, and quay cranes for a set of waiting vessels with the minimum cost regarding the time of departure of vessels.…”

Section: Related Workmentioning

confidence: 99%

A Comprehensive Modeling of the Discrete and Dynamic Problem of Berth Allocation in Maritime Terminals

Mnasri

Alrashidi

2021

Electronics

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In this study, the discrete and dynamic problem of berth allocation in maritime terminals, is investigated. The suggested resolution method relies on a paradigm of optimization with two techniques: heuristic and multi-agent. Indeed, a set of techniques such as the protocol of negotiation named contract net, the multi-agent interactions, and Worst-Fit arrangement technique, are involved. The main objective of the study is to propose a solution for attributing m parallel machines to a set of activities. The contribution of the study is to provide a detailed modeling of the discrete and dynamic berth allocation problem by establishing the corresponding models using a multi-agent methodology. A set of numerical experiments are detailed to prove the performance of the introduced multi-agent strategy compared with genetic algorithm and tabu search.

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“…Introduction. Container terminals play a vital role as representative logistics facilities for contemporary trade by handling inbound, outbound, and transshipment containers to and from the hinterland and sea [36,16]. Recent statistics recommend that the volume of global container trade is rising year by year, reaching 152 million TEU by 2019, global trade recovered strongly from the COVID-19 pandemic to a new record in 2021, with the momentum of growth hitting an all-time high in the first quarter of 2021, growing 10% year-over-year [32].…”

mentioning

confidence: 99%

“…The reactive strategy produces a reactive schedule which is used to adjust the original baseline schedule in real time once an uncertainty occurs, improve its scheduling recoverability accordingly [37,31]. Most of existing researches in dealing with uncertainties have adopted only one of the two strategies (Zeng et al [41]; Rodriguez-Molins et al [24]; Shang et al [25]; Liu et al [19]; Xiang et al [37]; Xiang et al [36]). The main reason is that most scholars focus on one type of uncertainty in BACAP research.…”

mentioning

confidence: 99%

“…Thus, this paper provides an integrated approach of proactive and reactive strategies for BACAP according to the different influence modes of uncertain combination on scheduling schemes, which support automated container terminal to cope with the uncertain combination, so as to meet actual demand and improve the quality of service. Currently, the optimization target of BACAP model under uncertain case in most studies is the cost or time issues [36,23], which cannot truly reflect actual demand of container terminal. In reality, different decision-makers tend to choose different coping decisions due to their own experiential knowledge structure and direct interests.…”

mentioning

confidence: 99%

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Integrated proactive-reactive approach and a hybrid adaptive large neighborhood search algorithm for berth and quay crane scheduling under uncertain combination

Zhu

2023

JIMO

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<p style='text-indent:20px;'>The integrated berth and quay crane scheduling problem is frequently encountered in port management issue, and the dynamic random data obtained by the container terminals under uncertain combination usually makes it unworkable to execute the scheduling. To promote sustainability and adaptivity of container terminals, this paper focuses on developing an integrated proactive-reactive approach for berth and quay crane scheduling under the fluctuation of vessels' arrival time and breakdown of quay crane. The problem is modelled as a two-stage mixed integer program where the baseline schedule with robustness is established in the first stage, and the recovery schedule is established in the second stage. This study aims to minimize the total management cost deviation and total time deviation of the terminal scheduling, so as to implement minimal changes compared with the baseline schedule. Therefore, the scheduling performance such as robustness, recoverability and adaptability is considered. To solve this model, a hybrid adaptive large neighborhood search (HALNS) algorithm framework combined with variable neighborhood search is developed, and the greedy algorithm is developed to construct the initial feasible solution. The performance evaluation tests of the proposed algorithm are performed on the three scales of benchmark. Computational results indicate the strength of solution methods and effectiveness of the proposed model.</p>

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An almost robust optimization model for integrated berth allocation and quay crane assignment problem

Cited by 40 publications

References 63 publications

A resilient, robust transformation of healthcare systems to cope with COVID-19 through alternative resources

A resilient, robust transformation of healthcare systems to cope with COVID-19 through alternative resources

A Comprehensive Modeling of the Discrete and Dynamic Problem of Berth Allocation in Maritime Terminals

Integrated proactive-reactive approach and a hybrid adaptive large neighborhood search algorithm for berth and quay crane scheduling under uncertain combination

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