Berth and quay crane allocation and scheduling problem with renewable energy uncertainty: A robust exact decomposition

Chargui, Kaoutar; Zouadi, Tarik; Sreedharan, Raja

doi:10.1016/j.cor.2023.106251

Cited by 11 publications

(2 citation statements)

References 27 publications

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“…The quay-crane-allocation problem (QCAP), initially introduced by Park and Kim [7], aims to integrate berth allocation and QC scheduling. Recently, it has been proven that the QCAP becomes effective if performed simultaneously with the BAP [8]. Figure 1 illustrates the basic concept of the QCAP, using a satellite image of the Ningbo container terminal as an example.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, maritime operations often involve significant costs, and even slight fluctuations in these uncertain parameters can result in substantial economic losses. Given this situation, the modeling of, and research into container port optimization under stochastic conditions are gradually becoming the focus of academic research [8,17,18].…”

Section: Introductionmentioning

confidence: 99%

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Distributionally Robust Programming of Berth-Allocation-with-Crane-Allocation Problem with Uncertain Quay-Crane-Handling Efficiency

Tang,

Liu,

et al. 2023

Sustainability

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In order to promote the efficient and intelligent construction of container ports, we focus on the optimization of berth-and-quay-crane (QC) allocation in tidal terminal operations. This paper investigates the quay-crane-profile-(QC-profile)-based assignment problem, and considers the uncertainty in QC profiles regarding QC efficiency for the first time. A mixed-integer programming (MIP) model is established for a discrete berth allocation with a crane-assignment problem (BACAP), considering the tide time window. We aim to minimize the total time loss caused by anchorage and the delay of vessels. Leveraging the theory of uncertainty optimization, the proposed deterministic model is extended into a stochastic programming (SP) model and a distributionally robust optimization (DRO) model, via the consideration of the random QC efficiency. To solve the proposed models, a column generation (CG) algorithm is employed, utilizing the mathematical method and subproblem-solving approach. The numerical experiments with different instances demonstrate that the DRO model yields a smaller variation in the objective function values, and the effectiveness of the CG method. The experimental results verify the robustness of the constructed models, and the efficiency of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributionally Robust Programming of Berth-Allocation-with-Crane-Allocation Problem with Uncertain Quay-Crane-Handling Efficiency

Tang,

Liu,

et al. 2023

Sustainability

View full text Add to dashboard Cite

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A novel robust decomposition algorithm for a profit-oriented production routing problem with backordering, uncertain prices, and service level constraints

Zouadi,

Chargui,

Zhani

et al. 2024

Ann Oper Res

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The Production Routing Problem (PRP) seeks optimal production and distribution planning that minimises costs and fulfils customer orders. Yet, existing literature often overlooks the potential impact on profitability. Achieving optimal profit does not necessarily imply meeting all customer orders. The cost-to-profit ratio should be considered when serving customer orders, as there are circumstances where it might be more profitable to cancel or backorder certain orders. Thus, this paper proposes, for the first time, a novel extension of PRP that maximises profit where demand is price-sensitive and allows order cancellation and backorders under service level targets. From on-field observations, price is inherently subject to uncertainty; thus, we propose a robust mathematical model for the problem that optimises the worst-case profit. To solve the problem, the paper proposes a decomposition algorithm that splits the problem into a master problem and a set of subproblems, enhanced by valid inequalities and warming up lower bounds to alleviate the model complexity. Through a series of computational tests, we prove the ability of the proposed algorithm to tighten the optimality gaps and alleviate computational time. An additional economic study is conducted to investigate how parameter variation affects profit and how sensitive it is to service level targets.

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Scheduling techniques for addressing uncertainties in container ports: A systematic literature review

Li,

Cai,

et al. 2024

Applied Soft Computing

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Berth and quay crane allocation and scheduling problem with renewable energy uncertainty: A robust exact decomposition

Cited by 11 publications

References 27 publications

Distributionally Robust Programming of Berth-Allocation-with-Crane-Allocation Problem with Uncertain Quay-Crane-Handling Efficiency

Distributionally Robust Programming of Berth-Allocation-with-Crane-Allocation Problem with Uncertain Quay-Crane-Handling Efficiency

A novel robust decomposition algorithm for a profit-oriented production routing problem with backordering, uncertain prices, and service level constraints

Scheduling techniques for addressing uncertainties in container ports: A systematic literature review

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