scholarly journals Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Li Wang ◽  
Xiaoning Zhu
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Model ◽  
Container Terminal ◽  
Solution Algorithm ◽  
Gantry Crane ◽  
Optimal Solutions ◽  
Scheduling Optimization ◽  
Crane Scheduling ◽  
Proposed Model ◽  
Container Handling

Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC.

scholarly journals Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Optimization Scheme ◽  
Long Distance ◽  
Proposed Model ◽  
Hybrid Heuristic Algorithm ◽  
Searching Ability

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

scholarly journals Locomotive Schedule Optimization for Da-qin Heavy Haul Railway

2015 ◽  
Vol 2015 ◽  
pp. 1-14
Author(s):  
Ruiye Su ◽  
Leishan Zhou ◽  
Jinjin Tang
Keyword(s):  
Optimization Model ◽  
Solution Algorithm ◽  
Rail Transportation ◽  
Model Case ◽  
Detention Time ◽  
Schedule Optimization ◽  
Proposed Model ◽  
Heavy Haul ◽  
The Stability ◽  
Heavy Haul Railway

The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP) hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP) can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid.

scholarly journals Coordinated Energy Management for Micro Energy Systems Considering Carbon Emissions Using Multi-Objective Optimization

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4414 ◽  
Author(s):  
Xing ◽  
Lin ◽  
Tan ◽  
Ju
Keyword(s):  
Demand Response ◽  
Carbon Emissions ◽  
Optimization Model ◽  
Operational Risk ◽  
Solution Algorithm ◽  
Objective Functions ◽  
Storage Devices ◽  
Proposed Model ◽  
And Storage ◽  
Operating Revenue

To promote the utilization of distributed resources, this paper proposes a concept of a micro energy system (MES) and its core structure with energy production, conversion, and storage devices. In addition, the effect of demand–response on the operation of a MES is studied. Firstly, based on uncertainties of a MES, a probability distribution model is introduced. Secondly, with the objectives of maximizing operating revenue, and minimizing operational risk and carbon emissions, a multi-objective coordinated dispatching optimization model was constructed. To solve this model, this paper linearizes objective functions and constraints via fuzzy satisfaction theory, then establishes the input–output matrix of the model and calculates the optimal weight coefficients of different objective functions via the rough set method. Next, a comprehensive dispatching optimization model was built. Finally, data from a MES in Longgang commercial park, Shenzhen City, were introduced for a case study, and the results show that: (1) A MES can integrate different types of energy, such as wind, photovoltaics, and gas. A multi-energy cycle is achieved via energy conversion and storage devices, and different energy demands are satisfied. Demand–response from users in a MES achieves the optimization of source–load interaction. (2) The proposed model gives consideration to the multi-objectives of operating revenue, operational risk, and carbon emissions, and its optimal strategy is obtained by using the proposed solution algorithm. (3) Sensitivity analysis results showed that risks can be avoided, to varying degrees, via reasonable setting of confidence. Price-based demand–response and maximum total emission allowances can be used as indirect factors to influence the energy supply structure of a MES. In summary, the proposed model and solution algorithm are effective tools for different decision makers to conceive of dispatching strategies for different interests.

An Integration Optimization for Berth Allocation and Quay Crane Scheduling Method Based on the Genetic and Ant Colony Algorithm

2014 ◽  
Vol 505-506 ◽  
pp. 940-944 ◽  
Author(s):  
Ri Dong Wang ◽  
Jin Xin Cao ◽  
Yang Wang ◽  
Xia Xi Li
Keyword(s):  
Optimization Model ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Operating Costs ◽  
Berth Allocation ◽  
Quay Crane Scheduling ◽  
Scheduling Optimization ◽  
Crane Scheduling ◽  
Scarce Resources ◽  
Scheduling Method

The berth and quay crane in port are scarce resources. The scheduling optimization of them affects the ship's operating costs directly. In this paper we build an integration optimization model of berth allocation and quay crane scheduling to minimize the operating costs of quay crane and operating costs of the ships. A new genetic and ant colony algorithm is designed to solve this model.

Quay crane scheduling for multiple hatches vessel considering double-cycling strategy

2019 ◽  
Vol 120 (2) ◽  
pp. 253-264 ◽  
Author(s):  
Junliang He ◽  
Hang Yu ◽  
Caimao Tan ◽  
Wei Yan ◽  
Chao Jiang
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Mixed Integer ◽  
Quay Crane Scheduling ◽  
Crane Scheduling ◽  
Content Type ◽  
Operation Efficiency ◽  
Double Cycling ◽  
Proposed Model ◽  
Operational Constraints

Purpose The development of mega container ships and operational pressures puts forward higher requirements on the operational ability of the container terminal. Accordingly, the purpose of this paper is to propose an effective method for quay crane (QC) scheduling of multiple hatches vessel considering double-cycling strategy to improve the operation efficiency and reduce the risk of delay. Design/methodology/approach A mixed integer programming model, which covers the main operational constraints in a container terminal, is formulated to solve the quay crane scheduling problem (QCSP) with a novel objective. Findings A case study is presented and a number of numerical experiments are conducted to validate the effectiveness of the proposed model. Meanwhile, management insights are proposed. The results demonstrate that the proposed method can efficiently solve QCSP in a container terminal, and an interesting finding is that reducing the stack layers on the vessel can improve the operation efficiency of QC. Originality/value A new mathematical model is proposed for QC scheduling at the operational level, which considers the constraints of double-cycling strategy, multiple hatches and hatch covers. The proposed model also provides methods to research the QC double-cycling problem considering the balance between energy cost and operation efficiency.

Ant Colony Optimization for Solving the Container Stacking Problem

2016 ◽  
Vol 6 (2) ◽  
pp. 81-101 ◽  
Author(s):  
Jalel Euchi ◽  
Riadh Moussi ◽  
Fatma Ndiaye ◽  
Adnan Yassine
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Model ◽  
Ant Colony Algorithm ◽  
Numerical Results ◽  
Ant Colony ◽  
Ant System ◽  
Container Stacking ◽  
Container Handling

In this paper, the authors study the Container Stacking Problem (CSP) which is one of the most important problems in marine terminal. An optimization model is developed in order to determine the optimal storage strategy for various container-handling schedules. The objective of the model is to minimize the distance between vessel berthing location and the storage positions of containers. The CSP is solved by an efficient ant colony algorithm based on MAX-MIN ant system variant. The performance of the algorithm proposed is verified by a comparison with ILOG CPLEX for small-sized instances. In addition, numerical results for real-sized instances proved the efficiency of the algorithm.

Optimization Model and Algorithm for Smart Distribution Grid Maintenance Scheduling

2013 ◽  
Vol 457-458 ◽  
pp. 1457-1462
Author(s):  
Wei Wei ◽  
Xing Ying Chen ◽  
Kai Chen ◽  
Chun Ning Wang ◽  
Kun Yu
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Maintenance Scheduling ◽  
Actual Situation ◽  
Distribution Grid ◽  
Improved Genetic Algorithm ◽  
Scheduling Optimization ◽  
Degree Constraint ◽  
Proposed Model ◽  
Smart Distribution Grid

According to the actual situation of maintenance scheduling for distribution network, with the development of smart distribution grid, a maintenance scheduling optimization model which aims at taking the minimum electricity quantity caused by maintenance interruption without violating any constraints is proposed in this paper. Considering the actual situation, the temporary maintenance application and the maintenance status of equipment (outage or charged) are proposed in the objective function. In terms of constraints, leading in emergency degree constraint makes it possible that the maintenance scheduling can be sequenced according to orders of priority, which conforms to the development of smart distribution grid better. Then by use of improved genetic algorithm the optimization problem is solved. The test results show that the proposed model and algorithm can effectively solve the maintenance scheduling optimization problem.

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