scholarly journals Berth Allocation and Quay Crane Assignment Under Uncertainties

2020 ◽  
Author(s):  
Caimao Tan ◽  
Junliang He ◽  
Yuancai Wang
Keyword(s):  
Stochastic Programming ◽  
Numerical Experiments ◽  
Programming Model ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Operations Planning ◽  
Proposed Model ◽  
Departure Time ◽  
Stochastic Programming Model ◽  
Quay Crane Assignment

The integration of berth allocation problem (BAP) and quay crane assignment problem (QCAP) is an cardinal seaside operations planning, which is susceptible to uncertainties, e.g. uncertain vessels arrival and maritime market. This paper addresses the integrated optimization of BAP and QCAP under uncertainties. A stochastic programming model is formulated for minimizing the waiting time and delay departure time of vessels. Besides, numerical experiments and scenario analysis are conducted to validate the effectiveness of the proposed model.

scholarly journals A Lexicographic Approach to Postdisaster Relief Logistics Planning Considering Fill Rates and Costs under Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Yajie Liu ◽  
Bo Guo
Keyword(s):  
Stochastic Programming ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Mixed Integer ◽  
Integer Optimization ◽  
Solution Algorithms ◽  
Evacuation Plans ◽  
Proposed Model ◽  
Transportation Assets ◽  
Stochastic Programming Model

Predicting the occurrences of earthquakes is difficult, but because they often bring huge catastrophes, it is necessary to launch relief logistics campaigns soon after they occur. This paper proposes a stochastic optimization model for post-disaster relief logistics to guide the strategic planning with respect to the locations of temporary facilities, the mobilization levels of relief supplies, and the deployment of transportation assets with uncertainty on demands. In addition, delivery plans for relief supplies and evacuation plans for critical population have been developed for each scenario. Two objectives are featured in the proposed model: maximizing the expected minimal fill rate of affected areas, where the mismatching distribution among correlated relief demands is penalized, and minimizing the expected total cost. An approximate lexicographic approach is here used to transform the bi-objective stochastic programming model into a sequence of single objective stochastic programming models, and scenario-decomposition-based heuristic algorithms are furthermore developed to solve these transformed models. The feasibility of the proposed bi-objective stochastic model has been demonstrated empirically, and the effectiveness of the developed solution algorithms has also been evaluated and compared to that of commercial mixed-integer optimization software.

Stochastic Programming Based on Traveling Salesman Problem with Stochastic Cost

2013 ◽  
Vol 321-324 ◽  
pp. 2076-2079
Author(s):  
Xiao Zheng Yang ◽  
Qing Chun Li ◽  
Lei Zhou ◽  
Hong Qi Hui
Keyword(s):  
Stochastic Programming ◽  
Traveling Salesman Problem ◽  
Programming Model ◽  
Real Life ◽  
Traveling Salesman ◽  
Factors Affecting ◽  
Logistics Distribution ◽  
Proposed Model ◽  
Stochastic Programming Model ◽  
Cost Factors

The research of traveling salesman problem (TSP) is important in logistics distribution. Because many stochastic cost factors affecting logistics distribution in real life, a class of stochastic programming model is considered in TSP in this paper. Through given a class of synthesizing effect functions which synthesis expectation and variance of cost factors, stochastic programming model of TSP with stochastic cost can be converted into a class of crisp programming models. A genetic algorithm based on real coding is used in an illustrative example. It is provided to show the effectiveness of the proposed model and method.

scholarly journals Accounting for Fairness in a Two-Stage Stochastic Programming Model for Kidney Exchange Programs

2018 ◽  
Vol 15 (7) ◽  
pp. 1491 ◽  
Author(s):  
Hyunwoo Lee ◽  
Seokhyun Chung ◽  
Taesu Cheong ◽  
Sang Song
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Deterministic Models ◽  
Two Stage ◽  
Total Utility ◽  
Exchange Programs ◽  
Kidney Exchange ◽  
Second Stage ◽  
Proposed Model ◽  
Stochastic Programming Model

Kidney exchange programs, which allow a potential living donor whose kidney is incompatible with his or her intended recipient to donate a kidney to another patient in return for a kidney that is compatible for their intended recipient, usually aims to maximize the number of possible kidney exchanges or the total utility of the program. However, the fairness of these exchanges is an issue that has often been ignored. In this paper, as a way to overcome the problems arising in previous studies, we take fairness to be the degree to which individual patient-donor pairs feel satisfied, rather than the extent to which the exchange increases social benefits. A kidney exchange has to occur on the basis of the value of the kidneys themselves because the process is similar to bartering. If the matched kidneys are not of the level expected by the patient-donor pairs involved, the match may break and the kidney exchange transplantation may fail. This study attempts to classify possible scenarios for such failures and incorporate these into a stochastic programming framework. We apply a two-stage stochastic programming method using total utility in the first stage and the sum of the penalties for failure in the second stage when an exceptional event occurs. Computational results are provided to demonstrate the improvement of the proposed model compared to that of previous deterministic models.

Optimization of Plane Slots Number for Container Yard Based on Two-Stage Stochastic Programming

2013 ◽  
Vol 807-809 ◽  
pp. 2845-2848
Author(s):  
Zi Jian Guo ◽  
Xu Hui Yu ◽  
Wen Yuan Wang ◽  
Guo Lei Tang
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Random Variable ◽  
Optimization Method ◽  
Low Carbon ◽  
Two Stage ◽  
The Sustainable Development ◽  
Proposed Model ◽  
Container Ports ◽  
Stochastic Programming Model

Appropriate plane slots number of the container yard is of great importance to the sustainable development of low-carbon container ports. Considering the container type, handling process, cost and benefit of unit yard space, etc., a two-stage stochastic programming model with the goal of maximizing the yard profit was established by choosing the maximum daily storage number of containers as a random variable. The maximum yard profit and the minimum penalty function are respectively chosen as the goal in the first and second stage. The example results show that the value obtained by the two-stage stochastic programming is smaller than that by the specification. The proposed model provides an optimization method for the determination of plane slots number through effectively lessening the influence of uncertainties and saving resource cost.

Optimal berth allocation under regular and emergent vessel arrivals

2020 ◽  
pp. 147509022093788
Author(s):  
Abbas Al-Refaie ◽  
Hala Abedalqader
Keyword(s):  
Waiting Time ◽  
Container Terminal ◽  
Allocation Problem ◽  
Container Terminals ◽  
Future Research ◽  
Satisfaction Level ◽  
Berth Allocation ◽  
Scheduling Problems ◽  
Berth Allocation Problem ◽  
Quay Crane Assignment

This research proposes two optimization models to deal with the berth allocation problem. The first model considers the berth allocation problem under regular vessel arrivals to minimize the flow time of vessels in the marine container terminal, minimize the tardiness penalty costs, and maximize the satisfaction level of vessels’ operators on preferred times of departure. The second model optimizes the berth allocation problem under emergency conditions by maximizing the number of assigned vessels, minimizing the vessel’s waiting time, and maximizing the satisfaction level on the served ships. Two real examples are provided for model illustration under regular and emergent vessel arrivals. Results show that the proposed models effectively provide optimal vessel scheduling in the terminal, reduce costs at an acceptable satisfaction level of vessels’ operators, decrease the waiting time of vessels, and shorten the delay in departures under both regular and emergent vessel arrivals. In conclusion, the proposed models may provide valuable assistance to decision-makers in marine container terminals on determining optimal berth allocation under daily and emergency vessel arrivals. Future research considers quay crane assignment and scheduling problems.

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