scholarly journals Solving methods for the quay crane scheduling problem at port of Tripoli-Lebanon.

2020 ◽  
Author(s):  
Ali Skaf ◽  
Sid Lamrous ◽  
Zakaria Hammoudan ◽  
Marie-Ange Manier
Keyword(s):  
Dynamic Programming Algorithm ◽  
Heuristic Method ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Scheduling Problem ◽  
Exact Methods ◽  
Three Solutions ◽  
Quay Crane Scheduling ◽  
Crane Scheduling

The quay crane scheduling problem (QCSP) is a global problem and all ports around the world seek to solve it, to get an acceptable time of unloading containers from the vessels or loading containers to the vessels and therefore reducing the docking time in the terminal. This paper proposes three solutions for the QCSP in port of Tripoli-Lebanon, two exact methods which are the mixed integer linear programming and the dynamic programming algorithm, to obtain the optimal solution and one heuristic method which is the genetic algorithm, to obtain near optimal solution within an acceptable CPU time. The main objective of these methods is to minimize the unloading or the loading time of the containers and therefore reduce the waiting time of the vessels in the terminals. We tested and validated our methods for small and large random instances. Finally, we compared the results obtained with these methods for some real instances in the port of Tripoli-Lebanon.

Supply Chain Scheduling with Transportation Cost on a Single Machine

2011 ◽  
Vol 382 ◽  
pp. 106-109
Author(s):  
Jing Fan
Keyword(s):  
Supply Chain ◽  
Single Machine ◽  
System Integration ◽  
Production Cost ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Programming Algorithm ◽  
Scheduling Problem ◽  
Supply Chain Scheduling

Supply chain scheduling problem is raised from modern manufacturing system integration, in which manufacturers not only process orders but also transport products to customer’s location. Therefore, the system ought to consider how to appropriately send finished jobs in batches to reduce transportation costs while considering the processing sequence of jobs to reduce production cost. This paper studies such a supply chain scheduling problem that one manufacturer produces with a single machine and deliveries jobs within limited transportation times to one customer. The objective function is to minimize the total sum of production cost and transportation cost. The NP hard property of the problem is proved in the simpler way, and the pseudo-dynamic programming algorithm in the literature is modified as the MDP algorithm to get the optimal solution which is associated with the total processing times of jobs.

scholarly journals Dynamic Programming and Heuristic for Stochastic Uncapacitated Lot-Sizing Problems with Incremental Quantity Discount

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Yuli Zhang ◽  
Shiji Song ◽  
Cheng Wu ◽  
Wenjun Yin
Keyword(s):  
Dynamic Programming ◽  
Lot Sizing ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Quantity Discount ◽  
Path Property ◽  
Commercial Solver

The stochastic uncapacitated lot-sizing problems with incremental quantity discount have been studied in this paper. First, a multistage stochastic mixed integer model is established by the scenario analysis approach and an equivalent reformulation is obtained through proper relaxation under the decreasing unit order price assumption. The proposed reformulation allows us to extend the production-path property to this framework, and furthermore we provide a more accurate characterization of the optimal solution. Then, a backward dynamic programming algorithm is developed to obtain the optimal solution and considering its exponential computation complexity in term of time stages, we design a new rolling horizon heuristic based on the proposed property. Comparisons with the commercial solver CPLEX and other heuristics indicate better performance of our proposed algorithms in both quality of solution and run time.

scholarly journals Two-Agent Single Machine Order Acceptance Scheduling Problem to Maximize Net Revenue

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jiaji Li ◽  
Yuvraj Gajpal ◽  
Amit Kumar Bhardwaj ◽  
Huangen Chen ◽  
Yuanyuan Liu
Keyword(s):  
Single Machine ◽  
Heuristic Method ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Order Acceptance ◽  
Net Revenue ◽  
Problem Instances ◽  
Tardy Jobs

The paper considers two-agent order acceptance scheduling problems with different scheduling criteria. Two agents have a set of jobs to be processed by a single machine. The processing time and due date of each job are known in advance. In the order accepting scheduling problem, jobs are allowed to be rejected. The objective of the problem is to maximize the net revenue while keeping the weighted number of tardy jobs for the second agent within a predetermined value. A mixed-integer linear programming (MILP) formulation is provided to obtain the optimal solution. The problem is considered as an NP-hard problem. Therefore, MILP can be used to solve small problem instances optimally. To solve the problem instances with realistic size, heuristic and metaheuristic algorithms have been proposed. A heuristic method is used to determine and secure a quick solution while the metaheuristic based on particle swarm optimization (PSO) is designed to obtain the near-optimal solution. A numerical experiment is piloted and conducted on the benchmark instances that could be obtained from the literature. The performances of the proposed algorithms are tested through numerical experiments. The proposed PSO can obtain the solution within 0.1% of the optimal solution for problem instances up to 60 jobs. The performance of the proposed PSO is found to be significantly better than the performance of the heuristic.

Exact methods for the quay crane scheduling problem when tasks are modeled at the single container level

2018 ◽  
Vol 99 ◽  
pp. 218-233 ◽  
Author(s):  
Mohamed Kais Msakni ◽  
Ali Diabat ◽  
Ghaith Rabadi ◽  
Mohamed Al-Salem ◽  
Mariam Kotachi
Keyword(s):  
Scheduling Problem ◽  
Exact Methods ◽  
Quay Crane Scheduling ◽  
Crane Scheduling

The Quay Crane Scheduling Problem With Stability Constraints

2018 ◽  
Vol 15 (3) ◽  
pp. 1399-1412 ◽  
Author(s):  
Zizhen Zhang ◽  
Ming Liu ◽  
Chung-Yee Lee ◽  
Jiahai Wang
Keyword(s):  
Scheduling Problem ◽  
Quay Crane Scheduling ◽  
Crane Scheduling

A heuristic for the quay crane scheduling problem based on contiguous bay crane operations

2012 ◽  
Vol 39 (12) ◽  
pp. 2915-2928 ◽  
Author(s):  
Zhiqiang Lu ◽  
Xiaole Han ◽  
Lifeng Xi ◽  
Alan L. Erera
Keyword(s):  
Scheduling Problem ◽  
Quay Crane Scheduling ◽  
Crane Scheduling

On the estimation of optimal state-of-charge trajectory for plug-in hybrid electric buses using trip information

2021 ◽  
pp. 095440702110410
Author(s):  
Naser Sina ◽  
Vahid Esfahanian ◽  
Mohammad Reza Hairi Yazdi
Keyword(s):  
Fuel Economy ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
State Of Charge ◽  
Estimation Accuracy ◽  
Programming Algorithm ◽  
Factors Affecting ◽  
Optimal State ◽  
Energy Management Systems ◽  
Hybrid Electric

Plug-in hybrid electric buses are a viable solution to increase the fuel economy. In this framework, precise estimation of optimal state-of-charge trajectory along the upcoming driving cycle appears to play a pivotal role in the way to approach the globally optimal fuel economy. This paper aims to conduct a parametric study on the key factors affecting the estimation of optimal state-of-charge trajectory, including trip information availability and trip segment distance, and to provide a guideline for the design and implementation of predictive energy management systems. To accomplish this, the dynamic programming algorithm is employed to obtain the solution of optimal control problem for the sampled driving cycles in a particular bus route. A large database comprising of driving features of the cycles and the optimal solution is developed which then is used to construct a neural network based estimator for obtaining the optimal state-of-charge trajectory. The main results show promising performance of the proposed method with about 76% reduction in the root mean square error of the estimated trajectory comparing to the linear state-of-charge trajectory assumption. Moreover, the robustness of the estimator is verified through simulation and it is observed that appropriate choice of trip segment distance is vital to improve the estimation accuracy, especially in case of uncertain prediction of trip information.

scholarly journals Hybrid of Hill Climbing and SAT Solving for Air Traffic Controller Shift Scheduling

2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Mirko Stojadinović
Keyword(s):  
Heuristic Method ◽  
Optimal Solution ◽  
Air Traffic ◽  
Hill Climbing ◽  
Hybrid Technique ◽  
Sat Solving ◽  
Shift Scheduling ◽  
Exact Methods ◽  
Air Traffic Controller ◽  
Three Phases

Modern computers solve many problems by using exact methods, heuristic methods and very often by using their combination. Air Traffic Controller Shift Scheduling Problem has been successfully solved by using SAT technology (reduction to logical formulas) and several models of the problem exist. We present a technique for solving this problem that is a combination of SAT solving and meta-heuristic method hill climbing, and consists of three phases. First, SAT solver is used to generate feasible solution. Then, the hill climbing is used to improve this solution, in terms of number of satisfied wishes of controllers. Finally, SAT solving is used to further improve the found solution by fixing some parts of the solution. Three phases are repeated until optimal solution is found. Usage of exact method (SAT solving) guarantees that the found solution is optimal; usage of meta-heuristic (hill climbing) increases the efficiency in finding good solutions. By using these essentially different ways of solving, we aim to use the best from both worlds. Results indicate that this hybrid technique outperforms previously most efficient developed techniques.

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