A novel robust exact decomposition algorithm for berth and quay crane allocation and scheduling problem considering uncertainty and energy efficiency

Chargui, Kaoutar; Zouadi, Tarik; Sreedharan, V. Raja; Fallahi, Abdellah El; Reghioui, Mohamed

doi:10.1016/j.omega.2023.102868

Cited by 14 publications

(4 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Constraint (17) ensures that at most N cranes are utilized in a period. Constraint (18) guarantees the continuity of QCs assigned to a vessel to prevent QCs from being assigned but not undertaking operational tasks. Constraint (19) ensures no crossing between adjacent QCs at any instant.…”

Section: Deterministic Modelmentioning

confidence: 99%

“…Agra and Rodrigues [17] formulated a distributionally robust two-stage model for BAP under uncertain handling time, and an exact decomposition algorithm was developed to solve the problem. Chargui et al [18] established a robust model to handle the uncertainty of renewable energy availability. The above literature adopts a proactive strategy to absorb the interference of uncertain factors by improving the robustness to obtain the system's stability.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Proactive-Reactive-Based Approach for Continuous Berth Allocation and Quay Crane Assignment Problems with Hybrid Uncertainty

Wang,

Cheng,

2024

JMSE

View full text Add to dashboard Cite

Port operations have been suffering from hybrid uncertainty, leading to various disruptions in efficiency and tenacity. However, these essential uncertain factors are often considered separately in literature during berth and quay crane assignments, leading to defective, even infeasible schedules. This paper addressed the integrated berth allocation and quay crane assignment problem (BACAP) with stochastic vessel delays under different conditions. A novel approach that combines both proactive and reactive strategies is proposed. First, a mixed-integer programming model is formulated for BACAP with quay crane maintenance activities under the ideal state of no delay. Then, for minor delays, buffer time is added to absorb the uncertainty of the arrival time of vessels. Thus, a robust optimization model for minimizing the total service time of vessels and maximizing the buffer time is developed. Considering that the schedule is infeasible when a vessel is seriously delayed, a reactive model is built to minimize adjustment costs. According to the characteristics of the problem, this article combined local search with the genetic algorithm and proposed an improved genetic algorithm (IGA). Numerical experiments validate the efficiency of the proposed algorithm with CPLEX and Squeaky Wheel Optimization (SWO) in different delay conditions and problem scales. An in-depth analysis presents some management insights on the coefficient setting, uncertainty, and buffer time.

show abstract

Section: Deterministic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Proactive-Reactive-Based Approach for Continuous Berth Allocation and Quay Crane Assignment Problems with Hybrid Uncertainty

Wang,

Cheng,

2024

JMSE

View full text Add to dashboard Cite

show abstract

“…They used the column generation algorithm to solve this model. Chargui et al [42] considered the impact of energy drive changes on the port equipment influenced by operating costs, and a corresponding robust model for BACAP was proposed. The classification of some BAP in the literature under uncertainty is shown in Table 1.…”

Section: Review Of the Literaturementioning

confidence: 99%

“…in which, ∆ could be replaced by Ψ, Γ and Ω according to the uncertainty set to be chosen. With Constraint (42), the [TSROBAP − US] could be represented as follows,…”

Section: Tsrobap-usmentioning

confidence: 99%

Two-Stage Robust Programming Modeling for Continuous Berth Allocation with Uncertain Vessel Arrival Time

Liu

et al. 2023

Sustainability

View full text Add to dashboard Cite

In order to mitigate the environmental pollution caused by sea freight, we focused on optimizing carbon emissions in container terminal operations. This paper establishes a mixed integer programming (MIP) model for a continuous berth allocation problem (CBAP) considering the tide time window. We aimed to minimize the total carbon emissions caused by the waiting time, consumption time and deviation to berth preference. In order to overcome the influence of an uncertain arrival time, the proposed MIP model was extended to mixed integer robust programming (MIRP) models, which applied a two-stage robust optimization (TSRO) approach to the optimal solution. We introduced an uncertainty set and scenarios to describe the uncertain arrival time. Due to the complexity of the resulting models, we proposed three particle swarm optimization (PSO) algorithms and made two novelties. The numerical experiment revealed that the robust models yielded a smaller variation in the objective function values, and the improved algorithms demonstrated a shorter solution time in solving the optimization problem. The results show the robustness of the constructed models and the efficiency of the proposed algorithms.

show abstract

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

View full text Add to dashboard Cite

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.

show abstract

A novel robust exact decomposition algorithm for berth and quay crane allocation and scheduling problem considering uncertainty and energy efficiency

Cited by 14 publications

References 58 publications

A Proactive-Reactive-Based Approach for Continuous Berth Allocation and Quay Crane Assignment Problems with Hybrid Uncertainty

A Proactive-Reactive-Based Approach for Continuous Berth Allocation and Quay Crane Assignment Problems with Hybrid Uncertainty

Two-Stage Robust Programming Modeling for Continuous Berth Allocation with Uncertain Vessel Arrival Time

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

Contact Info

Product

Resources

About