scholarly journals Modeling and Optimization in Resource Sharing Systems: Application to Bike-Sharing with Unequal Demands

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 47
Author(s):  
Xiaoting Mo ◽  
Xinglu Liu ◽  
Wai Kin (Victor) Chan
Keyword(s):  
Resource Sharing ◽  
Queueing Network ◽  
Significant Loss ◽  
Customer Churn ◽  
System A ◽  
Long Run ◽  
Proposed Model ◽  
Demand Node ◽  
Bike Sharing ◽  
Total Profit

The imbalanced distribution of shared bikes in the dockless bike-sharing system (a typical example of the resource-sharing system), which may lead to potential customer churn and lost profit, gradually becomes a vital problem for bike-sharing firms and their users. To resolve the problem, we first formulate the bike-sharing system as a Markovian queueing network with higher-demand nodes and lower-demand nodes, which can provide steady-state probabilities of having a certain number of bikes at one node. A model reduction method is then designed to reduce the complexity of the proposed model. Subsequently, we adopt an operator-based relocation strategy to optimize the reduced network. The objective of the optimization model is to maximize the total profit and act as a decision-making tool for operators to determine the optimal relocation frequency. The results reveal that it is possible for most of the shared bikes to gather at one low-demand node eventually in the long run under the influence of the various arrival rates at different nodes. However, the decrease of the number of bikes at the high-demand nodes is more sensitive to the unequal demands, especially when the size of the network and the number of bikes in the system are large. It may cause a significant loss for operators, to which they should pay attention. Meanwhile, different estimated values of parameters related with revenue and cost affect the optimization results differently.

scholarly journals Modelling and Optimization in Resource Sharing Systems: Application to Bike Sharing with Unequal Demands

2020 ◽  
Author(s):  
Xiaoting Mo ◽  
Xinglu Liu ◽  
Wai Kin (Victor) Chan
Keyword(s):  
Optimization Model ◽  
Resource Sharing ◽  
Network Models ◽  
Fundamental Principle ◽  
Great Loss ◽  
Imbalance Problem ◽  
Long Run ◽  
Demand Node ◽  
Bike Sharing ◽  
Term Performance

Although the dockless bike-sharing system, which can be regarded as a typical example of the resource-sharing system, has been increasingly popular for years with people especially in China, the imbalanced distribution of shared bikes gradually becomes a major problem for both bike-sharing companies and their customers. To solve the imbalance problem, we aim to investigate the long-term performance of a system under the influence of some key factors (with an emphasis on the unequal demand between different nodes), which can guide us to discover the causes of the problem and offer several valuable suggestions to the operators. According to the fundamental principle of a dockless bike-sharing system, we propose a model reduction method to reduce the complexity of the theoretical network models, which are developed based on the Markovian queueing theory with the consideration of higher-demand nodes and lower-demand nodes. The theoretical network models provide us with steady-state probabilities of having a certain number of bikes at one node, which are used as an important part of the optimization model for solving the imbalance problem by carrying out an operator-based relocation strategy. The objective of the optimization model is to maximize the total profit and determine the optimal relocation frequency. It is found that most of the shared bikes are possible to gather at one low-demand node eventually in the long run under the influence of the different arrival rates at different nodes, but the decrease of the number of bikes at the high-demand nodes is more sensitive to the unequal demands and may cause a great loss for operators, which should be payed attention to especially when solving the relocation problems.

Performance measurement and resource sharing among business sub-units in the presence of non-discretionary factors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rita Shakouri ◽  
Maziar Salahi
Keyword(s):  
Resource Sharing ◽  
Content Type ◽  
Development Level ◽  
Proposed Model ◽  
Decision Making Unit ◽  
Efficiency Estimation ◽  
Overall Efficiency ◽  
And Performance ◽  
The Right ◽  
The Impact

Purpose This paper aims to apply a new approach for resource sharing and efficiency estimation of subunits in the presence of non-discretionary factors and partial impacts among inputs and outputs in the data envelopment analysis (DEA) framework. Design/methodology/approach First, inspired by the Imanirad et al.’s model (2013), the authors consider that each decision-making unit (DMU) may consist of several subunits, that each of which can be affected by non-discretionary inputs. After that, the Banker and Morey’s model (1996) is used for modeling non-discretionary factors. For measuring performance of several subunits, which can be considered as DMUs, the aggregate efficiency is suggested. At last, the overall efficiency is computed and compared with each other. Findings One of the important features of proposed model is that each output in this model applies discretionary input according to its need; therefore, the result of this study will make it easier for the managers to make better decisions. Also, it indicates that significant predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the influence of non-discretionary input. Therefore, the proposed model provides a more reasonable and encompassing measure of performance in participating non-discretionary and discretionary inputs to better efficiency. An application of the proposed model for gaining efficiency of 17 road patrols is provided. Research limitations/implications More non-discretionary and discretionary inputs can be taken into consideration for a better analysis. This study provides us with a framework for performance measures along with useful managerial insights. Focusing upon the right scope of operations may help out the management in improving their overall efficiency and performance. In the recent highway maintenance management systems, the environmental differences exist among patrols and other geotechnical services under the climate diverse. Further, in some cases, there might exist more than one non-discretionary factor that can have different effects on the subunits’ performance. Practical implications The purpose of this paper was to measure the performance of a set of the roadway maintenance crews and to analyze the impact of non-discretionary inputs on the efficiency of the roadway maintenance. The application of the proposed model, on the one hand, showed that each output in this model uses discretionary input according to its requirement, and on the other hand, the result showed that meaningful predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the impact of non-discretionary input. Originality/value Providing information on resource sharing by taking into account non-discretionary factors for each subunit can help managers to make better decisions to increase the efficiency.

scholarly journals Modeling and Implementation of MPPT based Wind Energy System Using Cuckoo Search

2018 ◽  
Vol 7 (2.7) ◽  
pp. 671
Author(s):  
Kaleem SK ◽  
Rama Subbanna S
Keyword(s):  
Wind Energy ◽  
Control Strategy ◽  
Cuckoo Search ◽  
Energy System ◽  
System A ◽  
Wind Turbine System ◽  
Proposed Model ◽  
Wind Energy System ◽  
Mppt Controller ◽  
And Performance

This paper presents adjustable speed generators for wind turbines. In order to improve the potential and performance of wind turbine system this paper proposes a concept DFIG. Generally wind nature is not fixed it varies linearly w.r.t time, hence, a MPPT controller is proposed in this paper. This paper presents the DFIG wind energy system. A Control strategy implemented and controlled by framing rotor reference frame axis in terms of direct and quadrature axis coordinates. A PI based RSC and GSC controllers are introduced to control the power through the wind system to grid. This proposed model is implemented and verified by using Matlab/Simulink.  

SINGLE-MACHINE MULTIPLE-RECIPE PREDICTIVE MAINTENANCE

2013 ◽  
Vol 27 (2) ◽  
pp. 209-235 ◽  
Author(s):  
Yiwei Cai ◽  
John J. Hasenbein ◽  
Erhan Kutanoglu ◽  
Melody Liao
Keyword(s):  
Optimal Policy ◽  
Predictive Maintenance ◽  
Production Costs ◽  
Threshold Policy ◽  
Discrete Time Markov Chain ◽  
System A ◽  
Long Run ◽  
Monotonicity Result ◽  
Maintenance Policies ◽  
Discounted Costs

This paper studies a multiple-recipe predictive maintenance problem with M/G/1 queueing effects. The server degrades according to a discrete-time Markov chain and we assume that the controller knows both the machine status and the current number of jobs in the system. The controller's objective is to minimize total discounted costs or long-run average costs which include preventative and corrective maintenance costs, holdings costs, and possibly production costs. An optimal policy determines both when to perform maintenance and which type of job to process. Since the policy takes into account the machine's degradation status, such control decisions are known as predictive maintenance policies. In the single-recipe case, we prove that the optimal policy is monotone in the machine status, but not in the number of jobs in the system. A similar monotonicity result holds in the two-recipe case. Finally, we provide computational results indicating that significant savings can be realized when implementing a predictive maintenance policies instead of a traditional job-based threshold policy for preventive maintenances.

Analysis of Design Alternatives of End-of-Life Products Under Fractional Yields

2018 ◽  
pp. 18-41 ◽  
Author(s):  
Aditi D. Joshi ◽  
Surendra M. Gupta
Keyword(s):  
End Of Life ◽  
Goal Programming ◽  
Numerical Example ◽  
Purchase Cost ◽  
Design Alternatives ◽  
Proposed Model ◽  
Procurement Cost ◽  
Total Profit ◽  
Main Input ◽  
Disposal Cost

In this chapter, an advanced remanufacturing-to-order and disassembly-to-order (ARTODTO) system is considered to evaluate various design alternatives of end-of-life (EOL) products to meet products, components, and materials demands. There are uncertainties about the quantity, quality, and variety of returned EOL products, and these uncertainties lead to fractional disassembly yields. Since the main input to the system is EOL products, their quantities to be acquired is important, and should be determined such that they satisfy all the demands. The designs are evaluated based on four criteria: total profit, procurement cost, purchase cost, and disposal cost using goal programming (GP). A numerical example using EOL dryers is considered to illustrate the implementation of the proposed model.

Collaborative-Based Movie Recommender System—A Proposed Model

2021 ◽  
pp. 561-571
Author(s):  
Prajna Paramita Parida ◽  
Mahendra Kumar Gourisaria ◽  
Manjusha Pandey ◽  
Siddharth Swarup Rautaray
Keyword(s):  
Recommender System ◽  
System A ◽  
Proposed Model

scholarly journals Healthcare Operation Improvement Based on Simulation of Cooperative Resource Preservation Nets for None-Consumable Resources

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Soraia Oueida ◽  
Yehia Kotb ◽  
Seifedine Kadry ◽  
Sorin Ionescu
Keyword(s):  
Petri Net ◽  
Resource Sharing ◽  
Emergency Departments ◽  
Optimization Approach ◽  
Complex Dynamic Systems ◽  
Resource Preservation ◽  
Proposed Model ◽  
Modeling Techniques ◽  
Emergency Units ◽  
Major Bottleneck

Healthcare systems are growing very fast, especially emergency departments (EDs) which constitute the major bottleneck of these complex concurrent systems. Emergency departments, where patients arrive without any prior notice, are considered real-time complex dynamic systems. Enhancing these systems requires tailored modeling techniques and a process optimization approach. A new mathematical approach is proposed in order to help multiple emergency units cooperate and share none-consumable resources to achieve the required flow. To achieve the cooperation, the process is modeled by a new subclass of Petri nets. The new Petri net model was proposed in a previous work and is used in this study in order to tackle the problem of modeling and managing these emergency units. The proposed Petri net is named Resource Preservation Net (RPN). Few theorems and lemmas are proposed to support the proposed Petri net model and to prove the correctness of cooperation and resource sharing. In this contribution, a model of cooperative healthcare units is proposed to achieve sound resource sharing and collaboration. The objective function of the proposed model is to improve the key performance indicators: patients length of stay (LoS), resource utilization rates, and patients waiting time. The cooperation among multiple EDs is then proposed through the study of merging two or more units. The cooperative and noncooperative behavior are also studied through theorems of soundness, separability and serializability, and a proof of scalability.

scholarly journals Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Liu He ◽  
Tangyi Guo ◽  
Kun Tang
Keyword(s):  
Optimization Model ◽  
Dynamic Scheduling ◽  
Demand Forecasting ◽  
Optimal Solution ◽  
Coupling Model ◽  
Service Level ◽  
Demand Prediction ◽  
Dynamic Relationship ◽  
Proposed Model ◽  
Bike Sharing

System resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. This study innovatively introduces three types of invalid demand with negative effect including waiting, transfer, and abandoning, which consists of the total demand of bike-sharing system. Through exploring the dynamic relationship among users’ travel demands, the quantity and capacity of bikes at the rental points, the records of bicycles borrowed and returned, and the vehicle scheduling schemes, a demand forecasting model for bike-sharing is established. According to the predicted bikes and the maximum capacity limit at each rental point, an optimization model of scheduling scheme is proposed to reduce the invalid demand and the total scheduling time. A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). The proposed model is applied to a case study and the optimal solution set and corresponding Pareto front are obtained. The invalid demand is greatly reduced from 1094 to 26 by an effective scheduling of 3 rounds and 96 minutes. Empirical results show that the proposed model is able to optimize the resource allocation of bike-sharing, significantly reduce the invalid demand caused by the absence of bikes at the rental point such as waiting in a place, walking to other rental points, and giving up for other travel modes, and effectively improve the system service level.

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