scholarly journals Centralized Ambulance Diversion Policy Using Rolling-Horizon Optimization Framework to Minimize Patient Tardiness

Healthcare ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 266
Author(s):  
Sohye Baek ◽  
Young Hoon Lee ◽  
Seong Hyeon Park
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Time Interval ◽  
Rolling Horizon ◽  
Decentralized Optimization ◽  
Hospital System ◽  
Ambulance Diversion ◽  
Optimization Framework ◽  
The Impact ◽  
Rolling Horizon Optimization

Ambulance diversion (AD) is a common method for reducing crowdedness of emergency departments by diverting ambulance-transported patients to a neighboring hospital. In a multi-hospital system, the AD of one hospital increases the neighboring hospital’s congestion. This should be carefully considered for minimizing patients’ tardiness in the entire multi-hospital system. Therefore, this paper proposes a centralized AD policy based on a rolling-horizon optimization framework. It is an iterative methodology for coping with uncertainty, which first solves the centralized optimization model formulated as a mixed-integer linear programming model at each discretized time, and then moves forward for the time interval reflecting the realized uncertainty. Furthermore, the decentralized optimization, decentralized priority, and No-AD models are presented for practical application, which can also show the impact of using the following three factors: centralization, mathematical model, and AD strategy. The numerical experiments conducted based on the historical data of Seoul, South Korea, for 2017, show that the centralized AD policy outperforms the other three policies by 30%, 37%, and 44%, respectively, and that all three factors contribute to reducing patients’ tardiness. The proposed policy yields an efficient centralized AD management strategy, which can improve the local healthcare system with active coordination between hospitals.

Clustering for Innovative Business Model Design for Products and Services

2020 ◽  
pp. 125-148
Author(s):  
Jesús-Fabian López Pérez ◽  
Ana Elena De la Mora ◽  
Rosalba Trevino Reyes
Keyword(s):  
Factor Analysis ◽  
Programming Model ◽  
Aerospace Industry ◽  
Mixed Integer ◽  
Optimization Framework ◽  
Innovation Activities ◽  
Proposed Model ◽  
Rapid Product Development ◽  
Aerospace Companies ◽  
The Impact

Acceleration of technology evolution, customers' requests of agility in operations and rapid product development requires the supply chains to become more active and connected to attend clients and new markets. The chapter content is structured on three business use cases. The first section is related to the aerospace industry. The purpose is to identify the influence of quality and quantity of the supplier base in the innovation activities of aerospace companies participating in a cluster. Authors applied a framework based on factor analysis and multivariate linear regression to measure the impact of the quality and quantity of a set of suppliers. The second section is related to operation of Micro Finance institutions (MFIs). Authors design and propose a full-featured optimization framework based on a mixed integer programming model. They discuss the impact of the risk balancing and merits of the proposed model.

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

scholarly journals A Mixed Integer Linear Programming Method for Simultaneous Multi-Periodic Train Timetabling and Routing on a High-Speed Rail Network

2020 ◽  
Vol 12 (3) ◽  
pp. 1131
Author(s):  
Wenliang Zhou ◽  
Xiaorong You ◽  
Wenzhuang Fan
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
High Speed ◽  
Programming Model ◽  
Mixed Integer ◽  
High Speed Rail ◽  
Train Timetabling ◽  
Train Timetable ◽  
The Impact

To avoid conflicts among trains at stations and provide passengers with a periodic train timetable to improve service level, this paper mainly focuses on the problem of multi-periodic train timetabling and routing by optimizing the routes of trains at stations and their entering time and leaving time on each chosen arrival–departure track at each visited station. Based on the constructed directed graph, including unidirectional and bidirectional tracks at stations and in sections, a mixed integer linear programming model with the goal of minimizing the total travel time of trains is formulated. Then, a strategy is introduced to reduce the number of constraints for improving the solved efficiency of the model. Finally, the performance, stability and practicability of the proposed method, as well as the impact of some main factors on the model are analyzed by numerous instances on both a constructed railway network and Guang-Zhu inter-city railway; they are solved using the commercial solver WebSphere ILOG CPLEX (International Business Machines Corporation, New York, NY, USA). Experimental results show that integrating multi-periodic train timetabling and routing can be conducive to improving the quality of a train timetable. Hence, good economic and social benefits for high-speed rail can be achieved, thus, further contributing to the sustained development of both high-speed railway systems and society.

scholarly journals A rolling horizon optimization framework for the simultaneous energy supply and demand planning in microgrids

2015 ◽  
Vol 155 ◽  
pp. 485-501 ◽  
Author(s):  
Javier Silvente ◽  
Georgios M. Kopanos ◽  
Efstratios N. Pistikopoulos ◽  
Antonio Espuña
Keyword(s):  
Energy Supply ◽  
Supply And Demand ◽  
Rolling Horizon ◽  
Optimization Framework ◽  
Demand Planning ◽  
Rolling Horizon Optimization

scholarly journals Impact of demand response on BIPV and district multi-energy systems design in Singapore and Switzerland

2021 ◽  
Vol 2042 (1) ◽  
pp. 012096
Author(s):  
Christoph Waibel ◽  
Shanshan Hsieh ◽  
Arno Schlüter
Keyword(s):  
Demand Response ◽  
Programming Model ◽  
Systems Design ◽  
Energy Systems ◽  
Mixed Integer ◽  
Peak Shaving ◽  
Climate Conditions ◽  
Building Integrated Photovoltaics ◽  
Energy Hub ◽  
The Impact

Abstract This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.

scholarly journals Emission-Intensity-Based Carbon Tax and Its Impact on Generation Self-Scheduling

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 777 ◽  
Author(s):  
Ping Che ◽  
Yanyan Zhang ◽  
Jin Lang
Keyword(s):  
Electricity Market ◽  
Emission Intensity ◽  
Tax Policy ◽  
Programming Model ◽  
Carbon Tax ◽  
Electric Power Industry ◽  
Decomposition Algorithm ◽  
Mixed Integer ◽  
Tax Rate ◽  
The Impact

We propose an emission-intensity-based carbon-tax policy for the electric-power industry and investigate the impact of the policy on thermal generation self-scheduling in a deregulated electricity market. The carbon-tax policy is designed to take a variable tax rate that increases stepwise with the increase of generation emission intensity. By introducing a step function to express the variable tax rate, we formulate the generation self-scheduling problem under the proposed carbon-tax policy as a mixed integer nonlinear programming model. The objective function is to maximize total generation profits, which are determined by generation revenue and the levied carbon tax over the scheduling horizon. To solve the problem, a decomposition algorithm is developed where the variable tax rate is transformed into a pure integer linear formulation and the resulting problem is decomposed into multiple generation self-scheduling problems with a constant tax rate and emission-intensity constraints. Numerical results demonstrate that the proposed decomposition algorithm can solve the considered problem in a reasonable time and indicate that the proposed carbon-tax policy can enhance the incentive for generation companies to invest in low-carbon generation capacity.

scholarly journals UAVs Path Planning under a Bi-Objective Optimization Framework for Smart Cities

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1193
Author(s):  
Subrata Saha ◽  
Alex Elkjær Vasegaard ◽  
Izabela Nielsen ◽  
Aneta Hapka ◽  
Henryk Budzisz
Keyword(s):  
Programming Model ◽  
Smart Cities ◽  
Low Cost ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Cumulative Probability ◽  
Optimal Sequence ◽  
Optimization Framework ◽  
Benchmark Instances ◽  
Disaster Monitoring

Unmanned aerial vehicles (UAVs) have been used extensively for search and rescue operations, surveillance, disaster monitoring, attacking terrorists, etc. due to their growing advantages of low-cost, high maneuverability, and easy deployability. This study proposes a mixed-integer programming model under a multi-objective optimization framework to design trajectories that enable a set of UAVs to execute surveillance tasks. The first objective maximizes the cumulative probability of target detection to aim for mission planning success. The second objective ensures minimization of cumulative path length to provide a higher resource utilization goal. A two-step variable neighborhood search (VNS) algorithm is offered, which addresses the combinatorial optimization issue for determining the near-optimal sequence for cell visiting to reach the target. Numerical experiments and simulation results are evaluated in numerous benchmark instances. Results demonstrate that the proposed approach can favorably support practical deployability purposes.

scholarly journals Incorporating batching decisions and operational constraints into the scheduling problem of multisite manufacturing environments

2021 ◽  
Vol 12 (3) ◽  
pp. 345-364
Author(s):  
Sergio Ackermann ◽  
Yanina Fumero ◽  
Jorge M. Montagna
Keyword(s):  
Customer Service ◽  
Programming Model ◽  
Mixed Integer ◽  
Scheduling Problems ◽  
Efficient Operation ◽  
Batch Plants ◽  
Entire Complex ◽  
Operational Constraints ◽  
Manufacturing Environments ◽  
The Impact

In multisite production environments, the appropriate management of production resources is an activity of fundamental relevance to optimally respond to market demands. In particular, each production facility can operate with different policies according to its objectives, prioritizing the quality and standardization of the product, customer service, or the overall efficiency of the system; goals which must be taken into account when planning the production of the entire complex. At the operational level, in order to achieve an efficient operation of the production system, the integrated problem of batching and scheduling must be solved over all facilities, instead of doing it for each plant separately, as has been usual so far. Then, this paper proposes a mixed-integer linear programming model for the multisite batching and scheduling problems, where different operational policies are considered for multiple batch plants. Through two examples, the impact of policies on the decision-making process is shown.

scholarly journals A cost-effective decision-making algorithm for an RFID-enabled HMSC network design

2017 ◽  
Vol 117 (9) ◽  
pp. 1782-1799 ◽  
Author(s):  
Ahmed Mohammed ◽  
Qian Wang ◽  
Xiaodong Li
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Food Supply ◽  
Programming Model ◽  
Meat Products ◽  
Cost Effective ◽  
Mixed Integer ◽  
Food Supply Chain ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to investigate the economic feasibility of a three-echelon Halal Meat Supply Chain (HMSC) network that is monitored by a proposed radio frequency identification (RFID)-based management system for enhancing the integrity traceability of Halal meat products and to maximize the average integrity number of Halal meat products, maximize the return of investment (ROI), maximize the capacity utilization of facilities and minimize the total investment cost of the proposed RFID-monitoring system. The location-allocation problem of facilities needs also to be resolved in conjunction with the quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers. Design/methodology/approach First, a deterministic multi-objective mixed integer linear programming model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised solution based on four conflicting objectives as described above. Second, a stochastic programming model was developed and used for examining the impact on the number of Halal meat products by altering the value of integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for acquisition of non-inferior solutions obtained from the developed models. Furthermore, the Max-Min approach was used for selecting the best solution among them. Findings The research outcome shows the applicability of the developed models using a real case study. Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the HMSC network. Research limitations/implications This work addresses interesting avenues for further research on exploring the HMSC network design under different types of uncertainties and transportation means. Also, environmentalism has been becoming increasingly a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function. Practical implications The model can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management. Originality/value Although there were a few studies focusing on the configuration of a number of HMSC networks, this area is overlooked by researchers. The study shows the developed methodology can be a useful tool for designers to determine a cost-effective design of food supply chain networks.

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