scholarly journals Dynamic pricing with demand disaggregation for hotel revenue management

2021 ◽  
Author(s):  
Andrei M. Bandalouski ◽  
Natalja G. Egorova ◽  
Mikhail Y. Kovalyov ◽  
Erwin Pesch ◽  
S. Armagan Tarim
Keyword(s):  
Dynamic Pricing ◽  
Programming Model ◽  
Computer Experiments ◽  
Price Policy ◽  
Linear Constraints ◽  
Economic Consequences ◽  
Elastic Model ◽  
Computationally Efficient ◽  
Data Set ◽  
Dynamic Price

AbstractIn this paper we present a novel approach to the dynamic pricing problem for hotel businesses. It includes disaggregation of the demand into several categories, forecasting, elastic demand simulation, and a mathematical programming model with concave quadratic objective function and linear constraints for dynamic price optimization. The approach is computationally efficient and easy to implement. In computer experiments with a hotel data set, the hotel revenue is increased by about 6% on average in comparison with the actual revenue gained in a past period, where the fixed price policy was employed, subject to an assumption that the demand can deviate from the suggested elastic model. The approach and the developed software can be a useful tool for small hotels recovering from the economic consequences of the COVID-19 pandemic.

scholarly journals Bayesian Inference of Species Trees using Diffusion Models

2020 ◽  
Vol 70 (1) ◽  
pp. 145-161 ◽  
Author(s):  
Marnus Stoltz ◽  
Boris Baeumer ◽  
Remco Bouckaert ◽  
Colin Fox ◽  
Gordon Hiscott ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Numerical Algorithms ◽  
Diffusion Models ◽  
Model Parameters ◽  
Data Sets ◽  
Species Trees ◽  
Computationally Efficient ◽  
Data Set ◽  
Snp Data ◽  
Binary Markers

Abstract We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele frequency dynamics combined with novel numerical algorithms. The diffusion approach allows for analysis of data sets containing hundreds or thousands of individuals. The method, which we call Snapper, has been implemented as part of the BEAST2 package. We conducted simulation experiments to assess numerical error, computational requirements, and accuracy recovering known model parameters. A reanalysis of soybean SNP data demonstrates that the models implemented in Snapp and Snapper can be difficult to distinguish in practice, a characteristic which we tested with further simulations. We demonstrate the scale of analysis possible using a SNP data set sampled from 399 fresh water turtles in 41 populations. [Bayesian inference; diffusion models; multi-species coalescent; SNP data; species trees; spectral methods.]

scholarly journals Integrating Dynamic Pricing and Inventory Control for Fresh Agriproduct under Multinomial Logit Choice

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Xiong-zhi Wang ◽  
Wenliang Zhou
Keyword(s):  
Dynamic Pricing ◽  
Programming Model ◽  
Choice Model ◽  
Multinomial Logit ◽  
Linear Ordering ◽  
Stochastic Dynamic ◽  
Inventory Problem ◽  
Numerical Illustration ◽  
Dynamic Stochastic ◽  
Joint Pricing

In this article, we investigate a joint pricing and inventory problem for a retailer selling fresh agriproducts (FAPs) with two-period shelf lifetime in a dynamic stochastic setting, where new and old FAPs are on sale simultaneously. At the beginning of each period the retailer makes ordering decision for new FAP and sets regular and discount price for new and old inventories, respectively. After demand realization, the expired leftover is disposed and unexpired inventory is carried to the next period, continuing selling. Unmet demand of all FAPs is backordered. The objective is to maximize the total expected discount profit over the whole planning horizon. We present a price-dependent, stochastic dynamic programming model taking into account zero lead time, linear ordering costs, inventory holding, and backlogging costs, as well as disposal cost. Considering the influence of the perishability, we integrate a Multinomial Logit (MNL) choice model to describe the consumer behavior on purchasing fresh or nonfresh product. By way of the inverse of the price vector, the original formulation can be transferred to be jointly concave and tractable. Finally we characterize the optimal policy and develop effective methods to solve the problem and conduct a simple numerical illustration.

scholarly journals A Mathematical Programming Model to Determine Objective Weights for the Interval Extension of TOPSIS

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Hai Shen ◽  
Lingyu Hu ◽  
Kin Keung Lai
Keyword(s):  
Mathematical Programming ◽  
Input Data ◽  
Programming Model ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Mathematical Programming Model ◽  
Topsis Method ◽  
Data Set ◽  
Interval Extension ◽  
Interval Valued

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data. However, the weights associated with criteria are still subjectively assigned by decision makers. This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS. Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself. An illustrative example is performed to compare our results with that of existing literature.

scholarly journals Economic and environmental consequences of technical and institutional change in Dutch dairy farming

1997 ◽  
Vol 45 (3) ◽  
pp. 361-379
Author(s):  
P.B.M. Berentsen ◽  
G.W.J. Giesen ◽  
J.A. Renkema
Keyword(s):  
Milk Production ◽  
Programming Model ◽  
Dairy Farm ◽  
Price Policy ◽  
Positive Influence ◽  
High Price ◽  
Negative Consequences ◽  
Nutrient Losses ◽  
Price Support ◽  
Labour Income

A linear programming model of a dairy farm was used to explore the future for different types of Dutch dairy farms under different scenarios. The scenarios are consistent sets of changing factors that are considered external at farm level. The factors included are technical, such as efficiency of milk production and feed production, or institutional, such as national environmental legislation and EU market and price policy. Income and nutrient losses for farms differing in intensity and size are generated for the base year 1992 and for the year 2005. The results show that technical change up to the year 2005 has a positive influence on labour income as well as on nutrient losses. The increase of labour income is higher for farms with a higher total milk production in the basis situation. The influence of environmental policy on labour income and environmental results is bigger for farms with a higher intensity, as these farms have to take more measures to comply with governmental policy. Replacement of the price support policy for milk by a 2-price system with a high price for a restricted amount of milk and a low price for an unrestricted amount of milk has negative consequences for labour income, especially for intensive farms.

scholarly journals Determination of cost coefficients of priority-based water allocation linear programming model – a network flow approach

2013 ◽  
Vol 10 (12) ◽  
pp. 15033-15070
Author(s):  
F. N.-F. Chou ◽  
C.-W. Wu
Keyword(s):  
Network Flow ◽  
Water Allocation ◽  
Programming Model ◽  
Original System ◽  
Linear Constraints ◽  
Operating Rules ◽  
River Reservoir ◽  
Link Cost ◽  
Basin Water ◽  
The Cost

Abstract. This paper presents a method to establish the objective function of a network flow programming model for simulating river/reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and trans-basin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen Reservoirs joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.

scholarly journals Equivalent Transformation of Nonlinear Constraints to Linear Constraints in Petri Nets

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
YuFeng Chen ◽  
Abdulrahman Al-Ahmari ◽  
Chi Tin Hon ◽  
NaiQi Wu
Keyword(s):  
Linear Programming ◽  
Petri Nets ◽  
Integer Linear Programming ◽  
Programming Model ◽  
Linear Constraints ◽  
Linear Programming Model ◽  
Equivalent Transformation ◽  
Nonlinear Constraints ◽  
Nonlinear Constraint ◽  
Integer Linear Programming Model

This paper focuses on the enforcement of nonlinear constraints in Petri nets. An integer linear programming model is formulated to transform a nonlinear constraint to a minimal number of conjunctive linear constraints that have the same admissible marking space as the nonlinear one does in Petri nets. The obtained linear constraints can be easily enforced to be satisfied by a set of control places with a place invariant based method. The control places make up a supervisor that can enforce the given nonlinear constraint. For a case that the admissible marking space decided by a nonlinear constraint is nonconvex, another integer linear programming model is developed to obtain a minimal number of constraints whose disjunctions are equivalent to the nonlinear constraint with respect to the reachable markings. Finally, a number of examples are provided to demonstrate the proposed approach.

An Improved MapReduce Model for Computation-Intensive Task

2013 ◽  
Vol 756-759 ◽  
pp. 1701-1705
Author(s):  
Han Lin Sun
Keyword(s):  
Communication Channel ◽  
Programming Model ◽  
Machine Learning Algorithms ◽  
Fluctuation Analysis ◽  
Data Set ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Data Intensive ◽  
Parallel Programming Model ◽  
Mapreduce Model ◽  
Detrended Fluctuation

MapReduce is a widely adopted parallel programming model. The standard MapReduce model is designed for data-intensive processing. However, some machine learning algorithms are computation-intensive and time-consuming tasks which process the same data set repeatedly. In this paper, we proposed an improved MapReduce model for computation-intensive algorithms. The model is constructed from a service combination perspective. In the model, the whole task is divided into lots of subtasks taking account into the algorithms parameters, and the datagram with acknowledgement mechanism is used as the communication channel among cluster workers. We took the multifractal detrended fluctuation analysis algorithm as an example to demonstrate the model.

scholarly journals Determination of cost coefficients of a priority-based water allocation linear programming model – a network flow approach

2014 ◽  
Vol 18 (5) ◽  
pp. 1857-1872 ◽  
Author(s):  
F. N.-F. Chou ◽  
C.-W. Wu
Keyword(s):  
Network Flow ◽  
Water Allocation ◽  
Programming Model ◽  
Original System ◽  
Linear Constraints ◽  
Water Diversions ◽  
Operating Rules ◽  
River Reservoir ◽  
Link Cost ◽  
The Cost

Abstract. This paper presents a method to establish the objective function of a network flow programming model for simulating river–reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and transbasin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients, which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen reservoirs' joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.

scholarly journals The Austrian Corona Panel Project: monitoring individual and societal dynamics amidst the COVID-19 crisis

2020 ◽  
Author(s):  
Bernhard Kittel ◽  
Sylvia Kritzinger ◽  
Hajo Boomgaarden ◽  
Barbara Prainsack ◽  
Jakob-Moritz Eberl ◽  
...  
Keyword(s):  
Data Access ◽  
Economic Consequences ◽  
Process Data ◽  
Data Set ◽  
Domain Specific ◽  
Data Collection Process ◽  
The Social ◽  
The Individual ◽  
Austrian Population ◽  
Societal Dynamics

Abstract Systematic and openly accessible data are vital to the scientific understanding of the social, political, and economic consequences of the COVID-19 pandemic. This article introduces the Austrian Corona Panel Project (ACPP), which has generated a unique, publicly available data set from late March 2020 onwards. ACPP has been designed to capture the social, political, and economic impact of the COVID-19 crisis on the Austrian population on a weekly basis. The thematic scope of the study covers several core dimensions related to the individual and societal impact of the COVID-19 crisis. The panel survey has a sample size of approximately 1500 respondents per wave. It contains questions that are asked every week, complemented by domain-specific modules to explore specific topics in more detail. The article presents details on the data collection process, data quality, the potential for analysis, and the modalities of data access pertaining to the first ten waves of the study.

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