Risk-Averse Optimization for Resilience Enhancement Under Uncertainty

2020 ◽  
Author(s):  
Jiaxin Wu ◽  
Pingfeng Wang
Keyword(s):  
Large Scale ◽  
Risk Measure ◽  
Recovery Process ◽  
Recovery Phase ◽  
Mixed Integer ◽  
Network Systems ◽  
Additional Risk ◽  
Deterministic Equivalent ◽  
Study Results

Abstract With the growth of complexity and extent, large scale interconnected network systems, e.g., transportation networks or infrastructure networks, become more vulnerable towards external disturbances. Hence, managing potential disruptive events during design, operating, and recovery phase of an engineered system therefore improving the system’s resilience is an important yet challenging task. In order to ensure system resilience after the occurrence of failure events, this study proposes a mixed integer linear programming (MILP) based restoration framework using heterogenous dispatchable agents. Scenario based stochastic optimization (SO) technique is adopted to deal with the inherent uncertainties imposed on the recovery process from the nature. Moreover, different from conventional SO using deterministic equivalent formulations, additional risk measure is implemented for this study because of the temporal sparsity of the decision making in applications such as the recovery from extreme events. The resulting restoration framework involves with a large-scale MILP problem and thus an adequate decompaction technique, i.e., modified Langragian Relaxation, is also proposed in order to achieve tractable time complexity. Case study results based on the IEEE 37-buses test feeder demonstrate the benefits of using the proposed framework for resilience improvement as well as the advantages of adopting SO formulations.

scholarly journals Location Routing Problem with Consideration of CO2 Emissions Cost: A Case Study

2020 ◽  
Vol 21 (2) ◽  
pp. 225-234
Author(s):  
Ananda Noor Sholichah ◽  
Y Yuniaristanto ◽  
I Wayan Suletra
Keyword(s):  
Co2 Emissions ◽  
Time Windows ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Study Results

Location and routing are the main critical problems investigated in a logistic. Location-Routing Problem (LRP) involves determining the location of facilities and vehicle routes to supply customer's demands. Determination of depots as distribution centers is one of the problems in LRP.  In LRP, carbon emissions need to be considered because these problems cause global warming and climate change. In this paper, a new mathematical model for LRP considering CO2 emissions minimization is proposed. This study developed a new  Mixed Integer Linear Programming (MILP)  model for LRP with time windows and considered the environmental impacts.  Finally, a case study was conducted in the province of Central Java, Indonesia. In this case study, there are three depot candidates. The study results indicated that using this method in existing conditions and constraints provides a more optimal solution than the company's actual route. A sensitivity analysis was also carried out in this case study.

scholarly journals Anatomical, morphological and phytochemical properties of Aegopodium alpestre Ledeb.: a case study of Kazakhstan

2020 ◽  
Vol 48 (3) ◽  
pp. 1473-1482
Author(s):  
Elzira A. KYRBASSOVA ◽  
Akmaral A. SARTAYEVA ◽  
Elmira M. IMANOVA ◽  
Nurdana N. SALYBEKOVA ◽  
Gulraikhan E. ZHANTEYEVA ◽  
...  
Keyword(s):  
Large Scale ◽  
Inorganic Compounds ◽  
Biologically Active Substances ◽  
Biologically Active ◽  
High Concentration ◽  
Vegetative Organs ◽  
Study Results ◽  
Cultivation Practice ◽  
Active Substances

This article deals with the phytochemical, morphological and anatomical investigation of ethanol-based extracts derived from the leaves and stems of the Aegopodium alpestre. The vegetative organs of A. alpestre were conserved according to Strasburger-Fleµming method using a 1:1:1 mixture of alcohol-glycerin-water. A total of 1200 ethanol-based extracts (2 from leaves and 2 from stem tissues per plant) were prepared using the Soxhlet extractor. All extracts were used to identify organic and inorganic compounds in the leaves and stems of the studied plant. Contents of biologically active substances, microelements, vitamins and amino acids were determined. This article is the first paper to display very high concentration and diversity of vitamins (6 types), micronutrients (5 types), and aminoacids (13 types) in the leaves and steams of A. alpestre. Findings conclude that identification of biologically active substances in the above the ground vegetative organs of A. alpestre may be a common practice in the future. Considering the study results, A. alpestre may be used as a medicinal plant on a large scale. For this, the cultivation practice needs to be scaled up.

Building Reconstruction After Large-Scale Disasters A Case Study of Ishinomaki City After the Great East Japan Earthquake

2016 ◽  
Vol 11 (sp) ◽  
pp. 780-788 ◽  
Author(s):  
Michio Ubaura ◽  
◽  
Junpei Nieda ◽  
Masashi Miyakawa ◽  
Keyword(s):  
Land Use Planning ◽  
Urban Areas ◽  
Large Scale ◽  
Agricultural Land ◽  
Recovery Process ◽  
Great East Japan Earthquake ◽  
Planning System ◽  
Compact City ◽  
Building Reconstruction

In large-scale disasters and the subsequent recovery process, land usage and urban spatial forms change. It is therefore important to use this process as an opportunity to create a more sustainable spatial structure. This study considers the urban spatial transformations that took place after the Great East Japan Earthquake, their causes, and accompanying issues by investigating building construction in the recovery process. The authors discovered that individual rebuilding is primarily concentrated in vacant lots within the city’s existing urbanized areas. This is likely due to the spatial impact of the urban planning and agricultural land use planning system, the area division of urbanization promotion areas, and the urbanization restricted areas, all of which were in place prior to the disaster and which have guided development. On the other hand, there are areas severely damaged by tsunami in which there has been little reconstruction of housing that was completely destroyed. The authors concluded that building reconstruction in Ishinomaki City resulted in both the formation of a high-density compact city and also very low-density urban areas.

Study on the Scheduling Problem of Powder Painting Production - A Case Study

2010 ◽  
Vol 97-101 ◽  
pp. 2459-2464
Author(s):  
Zhang Yong Hu ◽  
Qiang Su ◽  
Jun Liu ◽  
Hai Xia Yang
Keyword(s):  
Large Scale ◽  
Production Efficiency ◽  
Production Performance ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Adaptive Search ◽  
Optimal Sequence ◽  
Integer Nonlinear Programming ◽  
Minlp Model

A large-scale powder-painting scheduling problem is explored. The purpose is to find out the optimal sequence of a number of batches that dynamically arrive from upstream processes within a given scheduling horizon. The objective is to enhance the production efficiency and decrease the production cost as well. To solve this problem, a mixed integer nonlinear programming (MINLP) model is constructed and an algorithm called greedy randomized adaptive search procedure (GRASP) is designed. Case studies demonstrate that the proposed approach can improve the production performance significantly.

scholarly journals Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

2019 ◽  
Vol 11 (17) ◽  
pp. 4713 ◽  
Author(s):  
Yuping Lin ◽  
Kai Zhang ◽  
Zuo-Jun Max Shen ◽  
Lixin Miao
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Cost Minimization ◽  
Transportation Network ◽  
Power Grid ◽  
Mixed Integer ◽  
Charging Infrastructure ◽  
Second Order Cone ◽  
Charging Stations

In 2017, Shenzhen replaced all its buses with battery e-buses (electric buses) and has become the first all-e-bus city in the world. Systematic planning of the supporting charging infrastructure for the electrified bus transportation system is required. Considering the number of city e-buses and the land scarcity, large-scale bus charging stations were preferred and adopted by the city. Compared with other EVs (electric vehicles), e-buses have operational tasks and different charging behavior. Since large-scale electricity-consuming stations will result in an intense burden on the power grid, it is necessary to consider both the transportation network and the power grid when planning the charging infrastructure. A cost-minimization model to jointly determine the deployment of bus charging stations and a grid connection scheme was put forward, which is essentially a three-fold assignment model. The problem was formulated as a mixed-integer second-order cone programming model, and a “No R” algorithm was proposed to improve the computational speed further. Computational studies, including a case study of Shenzhen, were implemented and the impacts of EV technology advancements on the cost and the infrastructure layout were also investigated.

Welfare-maximizing transmission capacity expansion under uncertainty

2021 ◽  
Vol 379 (2202) ◽  
pp. 20190436
Author(s):  
S. Wogrin ◽  
D. Tejada-Arango ◽  
A. Downward ◽  
A.B. Philpott
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Capacity Expansion ◽  
Computational Effort ◽  
Transmission Capacity ◽  
Mixed Integer ◽  
Deterministic Equivalent ◽  
Time Period ◽  
Expansion Plan ◽  
Programming Package

We apply the JuDGE optimization package to a multistage stochastic leader–follower model that determines a transmission capacity expansion plan to maximize expected social welfare of consumers and producers who act as Cournot oligopolists in each time period. The problem is formulated as a large-scale mixed integer programme and applied to a 5-bus instance over scenario trees of varying size. The computational effort required by JuDGE is compared with solving the deterministic equivalent mixed integer programme using a state-of-the-art integer programming package. This article is part of the theme issue ‘The mathematics of energy systems’.

Optimizing Skip Stop Service in Passenger Rail Transportation

2012 ◽  
Author(s):  
Samuel L. Sogin ◽  
Brennan M. Caughron ◽  
Samantha G. Chadwick
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Solution Space ◽  
Mixed Integer ◽  
Rail Transportation ◽  
Travel Times ◽  
Passenger Rail ◽  
Optimal Balance ◽  
Passenger Travel

Two-track passenger rail lines typically operate with all trains serving every station. Without additional infrastructure, transit planners have limited options to improve travel times. Service could be improved by operating a skip-stop service where trains only serve a subset of all the station stops. A skip-stop pattern must find an optimal balance between faster passenger travel times and lower service frequencies at each station. A mixed integer formulation is proposed to analyze this tradeoff; however, the mixed integer formulation could not scale efficiently to analyze a large scale commuter line. A genetic algorithm is presented to search the solution space incorporating a larger problem scope and complexity. In a case study of a Midwest commuter line, overall passenger travel time could be decreased by 9.5%. Both analyses can give insights to transit operators on how to improve their service to their customers and increase ridership.

scholarly journals Optimizing Number and Locations of Alternative-Fuel Stations Using a Multi-Criteria Approach

2019 ◽  
Vol 9 (1) ◽  
pp. 3715-3720 ◽  
Author(s):  
B. Badri-Koohi ◽  
R. Tavakkoli-Moghaddam ◽  
M. Asghari
Keyword(s):  
Alternative Fuels ◽  
Large Scale ◽  
Fossil Fuels ◽  
Net Present Value ◽  
Alternative Fuel ◽  
Optimal Number ◽  
Mixed Integer ◽  
Parameter Values ◽  
Flow Refueling

The transition to alternative fuels is obligatory due to the finite amount of available fossil fuels and their rising prices. However, the transition cannot be done unless enough infrastructure exists. A very important infrastructure is the fueling station. As establishing alternative-fuel stations is expensive, the problem of finding the optimal number and locations of initial alternative-fuel stations emerges and it is investigated in this paper. A mixed-integer linear programming (MILP) formulation is proposed to minimize the costs using net present value (NPV) technique. The proposed formulation considers the criteria of the two most common models in the literature for such a problem, namely P-median model and flow refueling location model (FRLM). A decision support system is developed for the users to be able to control the parameter values and run different scenarios. For case study purposes, the method is used to find the optimal number and locations of the alternative-fuel stations in the city of Chicago. Some data wrangling techniques are used to overcome the inability of the method to solve very large-scale problems.

scholarly journals Optimal Target Assignment with Seamless Handovers for Networked Radars

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4555
Author(s):  
Juhyung Kim ◽  
Doo-Hyun Cho ◽  
Woo-Cheol Lee ◽  
Soon-Seo Park ◽  
Han-Lim Choi
Keyword(s):  
Linear Programming ◽  
Large Scale ◽  
Time Windows ◽  
Mixed Integer ◽  
Network Systems ◽  
Detection Range ◽  
Radar Network ◽  
Target Assignment ◽  
Linear Programming Formulation ◽  
Optimal Target

This paper proposes a binary linear programming formulation for multiple target assignment of a radar network and demonstrates its applicability to obtain optimal solutions using an off-the-shelf mixed-integer linear programming solver. The goal of radar resource scheduling in this paper is to assign the maximum number of targets by handing over targets between networked radar systems to overcome physical limitations such as the detection range and simultaneous tracking capability of each radar. To achieve this, time windows are generated considering the relation between each radar and target considering incoming target information. Numerical experiments using a local-scale simulation were performed to verify the functionality of the formulation and a sensitivity analysis was conducted to identify the trend of the results with respect to several parameters. Additional experiments performed for a large-scale (battlefield) scenario confirmed that the proposed formulation is valid and applicable for hundreds of targets and corresponding radar network systems composed of five distributed radars. The performance of the scheduling solutions using the proposed formulation was better than that of the general greedy algorithm as a heuristic approach in terms of objective value as well as the number of handovers.

Sign in / Sign up

Export Citation Format

Share Document