scholarly journals Modeling Framework Simulating the TERRE Activation Optimization Function

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2966
Author(s):  
Christos Roumkos ◽  
Pandelis Biskas ◽  
Ilias Marneris

The Trans-European Replacement Reserve Exchange (TERRE) project is the European implementation project for exchanging Balancing Energy (BE) from Replacement Reserves (RR). Its main objective is to operate a common European platform that gathers all RR Balancing Energy Orders (BEOs) from Transmission System Operators’ (TSOs) local BE markets into a Common Merit Order List (CMOL). It provides an optimized allocation of RR, covering all TSOs’ RR BE needs, by executing the Activation Optimization Function (AOF). In this paper, the mathematical formulation of the AOF is presented, which explicitly incorporates all standard products and constraints that are provisioned in the approved implementation framework. The clearing problem is formulated as a Mixed Integer Linear Programming model and solved within an iterative algorithm for the handling of Paradoxically Accepted Orders (PAOs). The modeling framework allows the coordination of two distinct market setups, i.e., the self-dispatch and central dispatch. To this end, a BEO conversion pre-process is executed for markets applying the central-dispatch setup, in order to attain the BE quantities for inclusion in the CMOL. The proposed model is evaluated using a test case including six countries that participate in the TERRE project (Portugal, Spain, France, Great Britain, Switzerland, Italy) as well as Greece.

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo

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.


2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.


2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Amir-Mohammad Golmohammadi ◽  
Hasan Rasay ◽  
Zaynab Akhoundpour Amiri ◽  
Maryam Solgi ◽  
Negar Balajeh

Machine learning, neural networks, and metaheuristic algorithms are relatively new subjects, closely related to each other: learning is somehow an intrinsic part of all of them. On the other hand, cell formation (CF) and facility layout design are the two fundamental steps in the CMS implementation. To get a successful CMS design, addressing the interrelated decisions simultaneously is important. In this article, a new nonlinear mixed-integer programming model is presented which comprehensively considers solving the integrated dynamic cell formation and inter/intracell layouts in continuous space. In the proposed model, cells are configured in flexible shapes during the planning horizon considering cell capacity in each period. This study considers the exact information about facility layout design and material handling cost. The proposed model is an NP-hard mixed-integer nonlinear programming model. To optimize the proposed problem, first, three metaheuristic algorithms, that is, Genetic Algorithm (GA), Keshtel Algorithm (KA), and Red Deer Algorithm (RDA), are employed. Then, to further improve the quality of the solutions, using machine learning approaches and combining the results of the aforementioned algorithms, a new metaheuristic algorithm is proposed. Numerical examples, sensitivity analyses, and comparisons of the performances of the algorithms are conducted.


2020 ◽  
Vol 18 (4) ◽  
Author(s):  
Reza Babazadeh ◽  
Ali Sabbaghnia ◽  
Fatemeh Shafipour

: Blood and its products play an undeniable role in human life. In recent years, although both academics and practitioners have investigated blood-related problems, further enhancement is still warranted. In this study, a mixed-integer linear programming model was proposed for local blood supply chain management. A supply network, including temporary and fixed blood donation facilities, blood banks, and blood processing centers, was designed regarding the deteriorating nature of blood. The proposed model was applied in a real case in Urmia, Iran. The numerical results and sensitivity analysis of the key model parameters ensured the applicability of the proposed model.


2015 ◽  
Vol 42 (7) ◽  
pp. 490-502 ◽  
Author(s):  
Hediye Tuydes-Yaman ◽  
Oruc Altintasi ◽  
Nuri Sendil

Intersection movements carry more disaggregate information about origin–destination (O–D) flows than link counts in a traffic network. In this paper, a mathematical formulation is presented for O–D matrix estimation using intersection counts, which is based on an existing linear programming model employing link counts. The proposed model estimates static O–D flows for uncongested networks assuming no a priori information on the O–D matrix. Both models were tested in two hypothetical networks previously used in O–D matrix studies to monitor their performances assuming various numbers of count location and measurement errors. Two new measures were proposed to evaluate the model characteristics of O–D flow estimation using traffic counts. While both link count based and intersection count based models performed with the same success under complete data collection assumption, intersection count based formulation estimated the O–D flows more successfully under decreasing number of observation locations. Also, the results of the 30 measurement error scenarios revealed that it performs more robustly than the link count based one; thus, it better estimates the O–D flows.


2020 ◽  
Vol 10 (12) ◽  
pp. 4362 ◽  
Author(s):  
Junsu Kim ◽  
Hongbin Moon ◽  
Hosang Jung

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.


Author(s):  
Qiang Meng ◽  
Shuaian Wang ◽  
Zhiyuan Liu

A model was developed for network design of a shipping service for large-scale intermodal liners that captured essential practical issues, including consistency with current services, slot purchasing, inland and maritime transportation, multiple-type containers, and origin-to-destination transit time. The model used a liner shipping hub-and-spoke network to facilitate laden container routing from one port to another. Laden container routing in the inland transportation network was combined with the maritime network by defining a set of candidate export and import ports. Empty container flow is described on the basis of path flow and leg flow in the inland and maritime networks, respectively. The problem of network design for shipping service of an intermodal liner was formulated as a mixed-integer linear programming model. The proposed model was used to design the shipping services for a global liner shipping company.


Author(s):  
N Safaei ◽  
R Tavakkoli-Moghaddam ◽  
F Sassani

This paper presents a novel, multi-objective mixed-integer programming model for designing a cellular manufacturing system (CMS) that minimizes the total cost and maximizes the overall system reliability. In general, it is impossible to avoid production interruptions while handling machine breakdowns. In this situation, changing the process route dynamically can provide a quick response to meet production requirements. By assuming alternative process plans for operation—part requirements, the concept of the ‘reliable route’ proposed in the literature is extended. In a redundant reliability system with a series—parallel configuration, each reliable route is associated with an operation of a part (i.e. an operation—part) as a parallel subsystem. This route consists of a number of units or alternative machines allocated to cells in such a way that parts are processed with the maximum reliability for a given period of time. When an alternative machine breaks down, unprocessed parts are transferred to the next predetermined machine on the reliable route in order to complete their processes. While the reliable route approach increases the overall system reliability, the operational costs of the system also increase. To assess the present proposed model as a useful decision tool for the manager, various numerical examples are solved and analysed. Finally, the related computational results are reported.


Transport ◽  
2021 ◽  
Vol 36 (6) ◽  
pp. 444-462
Author(s):  
Jiaming Liu ◽  
Bin Yu ◽  
Wenxuan Shan ◽  
Baozhen Yao ◽  
Yao Sun

The yard template problem in container ports determines the assignment of space to store containers for the vessels, which could impact container truck paths. Actually, the travel time of container truck paths is uncertain. This paper considers the uncertainty from two perspectives: (1) the yard congestion in the context of yard truck interruptions, (2) the correlation among adjacent road sections (links). A mixed-integer programming model is proposed to minimize the travel time of container trucks. The reliable shortest path, which takes the correlation among links into account is firstly discussed. To settle the problem, a Shuffled Complex Evolution Approach (SCE-UA) algorithm is designed to work out the assignment of yard template, and the A* algorithm is presented to find the reliable shortest path according to the port operator’s attitude. In our case study, one yard in Dalian (China) container port is chosen to test the applicability of the model. The result shows the proposed model can save 9% of the travel time of container trucks, compared with the model without considering the correlation among adjacent links.


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