scholarly journals Maximize Expected Profits by Dynamic After-Sales Service Investment Strategy Based on Word-of-Mouth Marketing in Social Network Shopping

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Ying Yu ◽  
Jiaomin Liu ◽  
Jiadong Ren ◽  
Qian Wang ◽  
Cuiyi Xiao
Keyword(s):  
Optimal Control ◽  
Social Network ◽  
Control Problem ◽  
Control Strategy ◽  
Word Of Mouth ◽  
Investment Strategy ◽  
Negative Evaluation ◽  
Communication Model ◽  
Data Simulation ◽  
Optimal Control Strategy

This paper discusses how word-of-mouth marketing affects the profits of product sales in social network-based shopping under good after-sales service. First, a new word-of-mouth communication model based on silent evaluation, positive evaluation, and negative evaluation is proposed. Second, we use the way of increasing after-sales service to achieve high praise and thereby maximize the expected profits. Thus, the proportion control problem of after-sales service investment is modeled as an optimal control problem. Third, the existence of optimal control is proved, and an optimal control strategy for dynamic proportion of after-sales service investment is proposed. Fourth, through data simulation of different real-world networks, it is verified that the expected profits under the dynamic after-sales service strategy is higher than that under any uniform control strategy. Finally, sensitivity analysis is performed to explore how different parameters affect the expected profits.

scholarly journals Impulsive Control for Continuous-Time Markov Decision Processes

2015 ◽  
Vol 47 (1) ◽  
pp. 106-127 ◽  
Author(s):  
François Dufour ◽  
Alexei B. Piunovskiy
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Markov Decision Processes ◽  
Control Strategy ◽  
Continuous Time ◽  
Sufficient Conditions ◽  
Decision Processes ◽  
Optimal Control Strategy ◽  
Optimality Equation ◽  
Markov Decision

In this paper our objective is to study continuous-time Markov decision processes on a general Borel state space with both impulsive and continuous controls for the infinite time horizon discounted cost. The continuous-time controlled process is shown to be nonexplosive under appropriate hypotheses. The so-called Bellman equation associated to this control problem is studied. Sufficient conditions ensuring the existence and the uniqueness of a bounded measurable solution to this optimality equation are provided. Moreover, it is shown that the value function of the optimization problem under consideration satisfies this optimality equation. Sufficient conditions are also presented to ensure on the one hand the existence of an optimal control strategy, and on the other hand the existence of a ε-optimal control strategy. The decomposition of the state space into two disjoint subsets is exhibited where, roughly speaking, one should apply a gradual action or an impulsive action correspondingly to obtain an optimal or ε-optimal strategy. An interesting consequence of our previous results is as follows: the set of strategies that allow interventions at time t = 0 and only immediately after natural jumps is a sufficient set for the control problem under consideration.

scholarly journals Impulsive Control for Continuous-Time Markov Decision Processes

2015 ◽  
Vol 47 (01) ◽  
pp. 106-127 ◽  
Author(s):  
François Dufour ◽  
Alexei B. Piunovskiy
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Markov Decision Processes ◽  
Control Strategy ◽  
Continuous Time ◽  
Sufficient Conditions ◽  
Decision Processes ◽  
Optimal Control Strategy ◽  
Optimality Equation ◽  
Markov Decision

In this paper our objective is to study continuous-time Markov decision processes on a general Borel state space with both impulsive and continuous controls for the infinite time horizon discounted cost. The continuous-time controlled process is shown to be nonexplosive under appropriate hypotheses. The so-called Bellman equation associated to this control problem is studied. Sufficient conditions ensuring the existence and the uniqueness of a bounded measurable solution to this optimality equation are provided. Moreover, it is shown that the value function of the optimization problem under consideration satisfies this optimality equation. Sufficient conditions are also presented to ensure on the one hand the existence of an optimal control strategy, and on the other hand the existence of a ε-optimal control strategy. The decomposition of the state space into two disjoint subsets is exhibited where, roughly speaking, one should apply a gradual action or an impulsive action correspondingly to obtain an optimal or ε-optimal strategy. An interesting consequence of our previous results is as follows: the set of strategies that allow interventions at time t = 0 and only immediately after natural jumps is a sufficient set for the control problem under consideration.

Application of Optimal Control Strategy to Converter Gas Recovery System

2012 ◽  
Vol 38 (6) ◽  
pp. 1017 ◽  
Author(s):  
Jia-Yan ZHANG ◽  
Zhong-Hai MA ◽  
Xiao-Bin QIAN ◽  
Shao-Ming LI ◽  
Jia-Hong LANG
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Gas Recovery ◽  
Recovery System ◽  
Converter Gas

Optimal control strategy for cancer remission using combinatorial therapy: A mathematical model-based approach

2021 ◽  
Vol 145 ◽  
pp. 110789
Author(s):  
Parthasakha Das ◽  
Samhita Das ◽  
Pritha Das ◽  
Fathalla A. Rihan ◽  
Muhammet Uzuntarla ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Combinatorial Therapy ◽  
Model Based ◽  
Cancer Remission

scholarly journals Development of an Optimal Start Control Strategy for a Variable Refrigerant Flow (VRF) System

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 271
Author(s):  
Yusung Lee ◽  
Woohyun Kim
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Predictive Performance ◽  
Building Energy ◽  
Data Driven ◽  
Energy Usage ◽  
Optimal Control Strategy ◽  
Save Energy ◽  
Time Required ◽  
Optimal Control Methods

In this study, an optimal control strategy for the variable refrigerant flow (VRF) system is developed using a data-driven model and on-site data to save the building energy. Three data-based models are developed to improve the on-site applicability. The presented models are used to determine the length of time required to bring each zone from its current temperature to the set point. The existing data are used to evaluate and validated the predictive performance of three data-based models. Experiments are conducted using three outdoor units and eight indoor units on site. The experimental test is performed to validate the performance of proposed optimal control by comparing between conventional and optimal control methods. Then, the ability to save energy wasted for maintaining temperature after temperature reaches the set points is evaluated through the comparison of energy usage. Given these results, 30.5% of energy is saved on average for each outdoor unit and the proposed optimal control strategy makes the zones comfortable.

scholarly journals Greedy control of cascading failures in interdependent networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Malgorzata Turalska ◽  
Ananthram Swami
Keyword(s):  
Optimal Control ◽  
Complex Systems ◽  
Control Strategy ◽  
Cascading Failures ◽  
Optimal Control Strategy ◽  
Supercritical Regime ◽  
Interdependent Networks ◽  
Malicious Activity ◽  
Cross System ◽  
Made In

AbstractComplex systems are challenging to control because the system responds to the controller in a nonlinear fashion, often incorporating feedback mechanisms. Interdependence of systems poses additional difficulties, as cross-system connections enable malicious activity to spread between layers, increasing systemic risk. In this paper we explore the conditions for an optimal control of cascading failures in a system of interdependent networks. Specifically, we study the Bak–Tang–Wiesenfeld sandpile model incorporating a control mechanism, which affects the frequency of cascades occurring in individual layers. This modification allows us to explore sandpile-like dynamics near the critical state, with supercritical region corresponding to infrequent large cascades and subcritical zone being characterized by frequent small avalanches. Topological coupling between networks introduces dependence of control settings adopted in respective layers, causing the control strategy of a given layer to be influenced by choices made in other connected networks. We find that the optimal control strategy for a layer operating in a supercritical regime is to be coupled to a layer operating in a subcritical zone, since such condition corresponds to reduced probability of inflicted avalanches. However this condition describes a parasitic relation, in which only one layer benefits. Second optimal configuration is a mutualistic one, where both layers adopt the same control strategy. Our results provide valuable insights into dynamics of cascading failures and and its control in interdependent complex systems.

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