Research on Emergency Supplies Scheduling Problem with Robust Optimization Approach

2013 ◽  
Vol 694-697 ◽  
pp. 3462-3465
Author(s):  
Dong Qing Jiang ◽  
Qun Xiong Zhu
Keyword(s):  
Robust Optimization ◽  
Delay Time ◽  
Unmet Needs ◽  
Optimization Approach ◽  
Scheduling Problem ◽  
Paper Study ◽  
Vehicle Route Problem ◽  
Vehicle Route ◽  
Route Problem ◽  
Robust Counterpart

This paper study multiple warehouses emergency supplies dispatch problem. Emergency dispatch vehicles route problem is different from traditional vehicle route problem, it does not take minimization freight, driving distance or driving total time as the goal, but take a minimization unmet needs and delay time as the goal. We use robust operator to transfer multiple warehouses emergency dispatch model into robust counterpart model, and verifying the correctness of the model with number experiment.

scholarly journals Optimization of Earthwork Allocation Path as Vehicle Route Problem Based on Genetic Algorithm

2020 ◽  
Vol 165 ◽  
pp. 04057
Author(s):  
Naifu Deng ◽  
Xuyang Li ◽  
Yanmin Su
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Construction Projects ◽  
Vehicle Route Problem ◽  
Vehicle Route ◽  
Route Problem ◽  
Modified Genetic Algorithm ◽  
Global Optimal ◽  
The Cost ◽  
Engineering Projects

In civil engineering, earthwork, prior to the construction of most engineering projects, is a lengthy and time-consuming work involving iterative processes. The cost of many AEC (Architecture, Engineering and Construction) projects is highly dependent on the efficiency of earthworks (e.g. road, embankment, railway and slope engineering). Therefore, designing proper earthwork planning is of importance. This paper simplifies the earthwork allocation problem to Vehicle Route Problem (VRP) which is commonly discussed in the field of transportation and logistics. An optimization model for the earthwork allocation path based on the modified Genetic Algorithm with a self-adaptive mechanism is developed to work out the global optimal hauling path for earthwork. The research results also instruct the initial topographic shaping of the Winter Olympic Skiing Courses Project. Furthermore, this optimization model is highly compatible with other evolutionary algorithms due to its flexibility, therefore, further improvement in this model is feasible and practical.

scholarly journals Pengembangan Varian Model Vehicle Route Problem (VRP) Untuk Penentuan Rute Angkutan Laut Penumpang Studi Kasus Pt. Pelni (Persero)

2019 ◽  
Vol 26 (3) ◽  
pp. 125
Author(s):  
Imbang Danandjojo ◽  
B Kombaitan ◽  
Idwan Santoso ◽  
Ibnu Syabri
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Route Problem ◽  
Vehicle Route ◽  
Route Problem ◽  
Nearest Neighborhood ◽  
Genetic Algorithm Model

Penelitian ini bertujuan mengembangkan varian modelVRP untuk menyusun rute angkutan umum penumpang. Sebagai bahan pertimbangan adalah karakteristik rutenya tertutup yang berawal dan berakhir pada terminal atau pangkalan yang sama, karakteristik pelanggannya deterministik dengan volume permintaan layanan tetap dan dalam kurun waktu saturound trip tertentu, serta karakteristik kendaraan yang dioperasikan memiliki variasi kapasitas dan biaya operasi. Rute disusun untuk memperoleh efisiensi biaya operasional yang optimal, setiap jalur yang ada dalam jaringan pelayanan dilewati tepat satu kali dengan alasan pemberian frekuensi layanan yang sama untuk setiaplink pergerakan penumpang. Penyusunan rute dilakukan melalui dua tahap, yaitu tahap inisialisasi dengan pendekatan metoda Nearest Addition atau Nearest Neighborhood Heuristic dan tahap perbaikan dengan pendekatan metoda Genetic Algorithm. Model ini belum mempertimbangkan adanya pola rute dengan naik-turun penumpang yang dinamis, serta kecepatan dan waktu tempuh kendaraan yang bersifat stokastik, permintaan pergerakan penumpang setiap jalur yang bersifat stokastik, ataupun jumlah pelabuhan dalam jaringan pelayanan yang bersifat stokastik. Sehingga membuka peluang penelitian lebih lanjut. Hasil penelitian menunjukkan bahwa dengan penyusunan ulang rute pelayanan kapal-kapal milik PELNI, total biaya operasional seluruh kapal dapat ditekan jauh lebih efisien hingga mencapai 64,38% dari total biaya aktual. Sedangkan dari sisi total jarak tempuh, dapat ditekan lebih efektif hingga mencapai 59,64% dari total jarak tempuh aktual. Kata kunci: VRP, angkutan laut penumpang, efisiensi biaya, efektivitas jaringan

A robust optimization approach for an artillery fire-scheduling problem under uncertain threat

2018 ◽  
Vol 125 ◽  
pp. 23-32 ◽  
Author(s):  
Yong Baek Choi ◽  
Suk Ho Jin ◽  
Kyung Sup Kim ◽  
Byung Do Chung
Keyword(s):  
Robust Optimization ◽  
Optimization Approach ◽  
Scheduling Problem

scholarly journals Domesticating Homecare Services; Vehicle Route Problem Solver Displaced

2016 ◽  
Vol 4 (2) ◽  
pp. 41 ◽  
Author(s):  
Jenny Melind Bergschöld
Keyword(s):  
Financial Control ◽  
Problem Solver ◽  
Vehicle Route Problem ◽  
Vehicle Route ◽  
Route Problem ◽  
The Everyday ◽  
Everyday Work ◽  
Problem Solvers ◽  
Optimal Driving

<p>This article presents a case study of a vehicle route problem solver in the context of homecare work. Vehicle route problem solvers are technologies that calculate geographically rational driving routes. Primarily framed as tools for financial control, they have been tested in homecare services with good results under controlled circumstances. However, they have not been studied as part of users’ everyday work after implementation. The case study shows how, through processes of domestication, the vehicle route problem solver becomes unable to provide homecare workers with ‘optimal’ driving routes. Additionally, it shows how this ‘malfunction’ renders it understood as inconsequential to the very activities it was designed to support which ultimately leads to its removal from driving route production processes. The results highlight the importance of carefully studying how vehicle route problem solvers and other technologies interact with the everyday lives of those who are meant to benefit from them.</p>

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

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