Coordinated planning in revenue management

Revenue management has been applied in service industries for more than thirty years. Since then, revenue management has been transferred to other industries like manufacturing or e- fulfillment. Short-term revenue management decisions are taken based on other, longer-term decisions such as decisions about actual capacity, segment-based prices or the price fences in place. While optimization approaches have been developed for each of these planning tasks in isolation, existing approaches typically do not consider interactions between planning tasks. This thesis considers coordinated planning in revenue management, that is the interaction of revenue management decisions with other planning tasks. First, we provide an overview of both the literature on coordinated decision making in the context of revenue management in different industries, and the literature on existing frameworks, which aim to structure the planning tasks around revenue management. We find that the planning tasks relevant to revenue management differ across the industries considered. Moreover, planning tasks are relevant on different hierarchical levels in different industries. We discuss an approach for an industry-independent framework. Based on the relevant planning tasks identified, we investigate the long-term performance of revenue management and therefore the integration of revenue management and customer relationship management. We present a stochastic dynamic programming approach, where the firm’s allocation decision impacts future customer demands by influencing the repurchase probabilities of customers, depending on whether their request has been accepted or rejected. We show that a protection level policy is not necessarily optimal in a two-period setting. In a numerical study, we find that the value of looking ahead in time is low on average but may be substantial in some scenarios. However, the benefit from regular demand updates is considerably higher than the additional value of looking ahead in time on average. Lastly, we investigate the interaction of revenue management and fencing. We account for the trade-off between price-driven demand leakage on the one hand and costs for fencing on the other hand. We show that fencing decisions have an impact on the optimal capacity allocation, but that this is not the case vice versa as the fencing decision does not depend on the allocation decision. Taking both decisions sequentially is therefore optimal. We extend our approach in order to account for additional stock-out-based demand substitution. Then, both decisions depend on each other and firms should take both decisions simultaneously

Joint determination of process mean, price differentiation, and production decisions with demand leakage: A multi-objective approach

The selection of an optimal process mean is an important problem in production planning and quality control research. Most of the literature in this area has focused on the single objective problem of maximizing the profit for a fixed exogenous price. However, it is known that considering multiple objectives (such as gross income from sales, profit, and expected product uniformity) while allowing process mean, production and pricing to vary can significantly improve the profitability and performance of a firm. This article addresses this multi-objective problem while allowing the firm to sell two classes of products at differentiated prices based on their quality characteristics. These products are sold at differentiated prices depending upon their quality characteristics into primary and secondary markets at full and discounted prices respectively. Any nonconforming items are reworked at an additional cost. Due to customers heterogeneity, the firm experiences demand leakage between the two market segments. The proposed joint decision control for the firm includes the joint determination of full and discounted prices, the process mean selection, and the production quantities for each of the two product classes along with expected reworked items. A mathematical formulation of the objectives is first provided and then the multi-objective problem is transformed into a goal-programming problem. A solution procedure is developed using simulation-based optimization to identify Pareto-optimal solutions. Some important characteristics of the solution procedure are discussed and the performance of the approach is corroborated through detailed numerical experiments. 2016 Elsevier Inc.This publication was made possible by the support of an NPRP grant no. 4-173-5-025 from the Qatar National Research Fund . The statements made herein are solely the responsibility of the authors.Scopu

A Study in Three Practical Management Science Problems

This study of practical problems in Management Science (MS) describes novel mathematical models for three different decision settings. It addresses questions of: (a) what optimal route should be taken through a time-windows and topographically complex network; (b) what optimal sequencing of scheduled surgeries best coordinates flow of patients through central recovery; and (c) what prices should be charged and what stock amounts should be produced for two markets or channels to maximize profit explicitly, given various capacity and uncertainty conditions. The first problem is in a sport analytics context, using a novel Integer Programming and big data from Whistler-Blackcomb ski resort. The second is to coordinate dozens of surgeries at London Health Sciences Centre, using a novel Constraint Programming model mapped to and parameterized with hospital data, including a tool for visualizing process and patient flow. The third problem is relevant to almost any business with a secondary market or sales channel, as it helps them identify profit optimal prices based on simple demand estimates and cost information they can easily provide for their own setting. The studies use fundamentally different operational research techniques, in each case uniquely extended to the problem setting. The first two are combinatorial problems, neither one extremely beyond human cognitive ability, and both involving lots of uncertainty, and thus the sort of problem managers tend to dismiss as not efficient or practical to solve analytically. We show in the first study that vastly more skiers could achieve the challenge by following our route recommendation, unintuitive as are some of its elements, initially. In the second study, our scheduling model consistently outperforms currently unstructured-independent approach at the hospital. The final study is mathematical but demonstrates that by considering distinct market costs in pricing a firm can invariably earn more profit

Worldscan; a model for international economic policy analysis

WorldScan is a recursively dynamic general equilibrium model for the world economy, developed for the analysis of long-term issues in international economics. The model is used both as a tool to construct long-term scenarios and as an instrument for policy impact assessments, e.g. in the fields of climate change, economic integration and trade. In general, with each application WorldScan is also adapted. This publication brings the model changes together, explains the model's current structure and illustrates the model's usage with some applications.

Priorities for Pig Research in Southeast Asia and the Pacific to 2010

Livestock Production/Industries, Research and Development/Tech Change/Emerging Technologies,

Strategic and Tactical Crude Oil Supply Chain: Mathematical Programming Models

Crude oil industry very fast became a strategic industry. Then, optimization of the Crude Oil Supply Chain (COSC) models has created new challenges. This fact motivated me to study the COSC mathematical programming models. We start with a systematic literature review to identify promising avenues. Afterwards, we elaborate three concert models to fill identified gaps in the COSC context, which are (i) joint venture formation, (ii) integrated upstream, and (iii) environmentally conscious design

The Conservation Reserve Program: Economic Implications for Rural America

This report estimates the impact that high levels of enrollment in the Conservation Reserve Program (CRP) have had on economic trends in rural counties since the program's inception in 1985 until today. The results of a growth model and quasi-experimental control group analysis indicate no discernible impact by the CRP on aggregate county population trends. Aggregate employment growth may have slowed in some high-CRP counties, but only temporarily. High levels of CRP enrollment appear to have affected farm-related businesses over the long run, but growth in the number of other nonfarm businesses moderated CRP's impact on total employment. If CRP contracts had ended in 2001, simulation models suggest that roughly 51 percent of CRP land would have returned to crop production, and that spending on outdoor recreation would decrease by as much as $300 million per year in rural areas. The resulting impacts on employment and income vary widely among regions having similar CRP enrollments, depending upon local economic conditions.Community/Rural/Urban Development, Land Economics/Use,

Electronic supply chain management systems in managing the bullwhip effect on selected fast moving consumer goods.

Ph. D. University of KwaZulu-Natal, Durban 2014.The amplitude in order variability as orders surge upstream a supply chain epitomises a phenomenon commonly called the bullwhip effect. The real consumer demand orders are comparatively and tentatively evinced less variability while trading supply chain members on the midstream and upstream stages experience the amplified order vacillations. The oscillator effect reveals a number of pernicious problems throughout the supply chain networks, as downstream sites include harmful bloated inventory and shortages with poor customer service, and the midstream and upstream sites depict the disharmonic capacity on improper planning and inconsistent scheduling in production. This study investigates the selected fast moving consumer goods (FMCG) industry on the amplified consumer demand order variability as orders cascade from downstream (retailers) to the midstream as well as upstream sites of the supply chain network.The effect of electronically-enabled supply chain management (e-SCM) systems remains the central hypothesis for instant information sharing on inventory positioning, integrated supply chain management processes and improved profitability through positive performance targets and outcomes across supply chain trading partners. The main objective aims to understand the on extent of the relationship to which the phenomenon of bullwhip effect can be explained by e-SCM system diffusion, optimal inventory positioning, strategic information sharing and global optimisation strategies. These seamless linkages between supply chain partners seem to entrench velocity on quasi-real-time information flow in consumer demand and supply sides, inventory status and availability, and capacity availability. This study found empirical research evidence on e-SCM systems that retail supply chain businesses have fastidiously adapted to technology clockspeed for the last five years. The majority of the respondents (92%) for both upstream and downstream echelon categories agreed that e-SCM systems have a significant role to play in mitigating the consumer demand order variability in the supply chain network. This study further discovered that the migration from in-house IT systems to integrated e-SCM systems (65%) would entrench close integration of information exchange and processes across different parts of the organisation and inter-organisational linkages. The e-SCM systems diffusion also depicted a positive linear relationship to the extent to which the organisations efficiently and timeously communicate the future strategic needs and demand order replenishments throughout the entire supply chain network. However, the access to advance economic information negatively related to e-SCM systems with the virtue of legal constraints and template-based information attachments