Quantity-setting competition with differentiated goods under uncertain demand

We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that the firms produce differentiated goods and that there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

Flexibility and leadership advantages in a model with uncertain demand

We consider a differentiated Stackelberg model with demand uncertainty only for the first mover. We study the advantages of flexibility over leadership as the degree of the differentiation of the goods changes.

Robust rolling stock under uncertain demand in rapid transit networks

This paper focuses on the railway rolling stock circulation problem in rapid transit networks where the known demand and train schedule must be met by a given fleet. In rapid transit networks the frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The previous circumstances and the reduced capacity of the depot stations and that the rolling stock is shared between the different lines, force the introduction of empty trains and a careful control on shunting operation. In practice the future demand is generally unknown and the decisions must be based on uncertain forecast. We have developed a stochastic rolling stock formulation of the problem. The computational experiments were developed using a commercial line of the Madrid suburban rail network operated by RENFE (The main Spanish operator of suburban trains of passengers). Comparing the results obtained by deterministic scenarios and stochastic approach some useful conclusions may be obtained.

A simulation-based algorithm for optimal pricing policy under demand uncertainty

We propose a simulation-based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high-dimensional parameters, it uses the efficient smoothed functional gradient estimator.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Techniques to effectively buffer schedules in the face of uncertainties

Resource assignment and scheduling is a difficult task when job processing times are stochastic, and resources are to be used for both known and unknown demand. To operate effectively within such an environment, several novel strategies are investigated. The first focuses upon the creation of a robust schedule, and utilises the concept of strategically placed idle time (i.e. buffering). The second approach introduces the idea of maintaining a number of free resources at each time, and culminates in another form of strategically placed buffering. The attraction of these approaches is that they are easy to grasp conceptually, and mimic what practitioners already do in practice. Our extensive numerical testing has shown that these techniques ensure more prompt job processing, and reduced job cancellations and waiting time. They are effective in the considered setting and could easily be adapted for many real life problems, for instance those in health care. This article has more importantly demonstrated that integrating the two approaches is a better strategy and will provide an effective stochastic scheduling approach.

Essays on supply chain's flexibility: a real options approach

A presente tese investiga o processo de tomada de decisão na gestão de cadeias de abastecimento, utilizando um quadro de análise de opções reais. Especificamente, estudamos tópicos como o nível de inventário ideal para protecção contra a incerteza da procura, o momento para implementação de capacidade flexível em mercados onde existe complexidade no mix de produtos, o tempo para o reforço do factor trabalho visando requisitos de serviço ao mercado, e as decisões entre integração e outsourcing num ambiente de incerteza. Foram usadas metodologias de tempo discreto e contínuo para identificar o valor ideal e o calendário das opções a adoptar, quando a procura é estocástica. Além disso, foram considerados os efeitos dos requisitos dos mercados, como a complexidade na oferta de produtos e o nível de serviço. A procura é representada recorrendo a diferentes processos estocásticos, o impacto de saltos inesperados também é explorado, reforçando a generalização dos modelos a diferentes condições de negócio. A aplicabilidade dos modelos que apresentamos permite a diversificação e o enriquecimento da literatura sobre a abordagem de opções reais, no âmbito das cadeias de abastecimento. Níveis de inventário flexíveis e capacidades flexíveis são característicos das cadeias de abastecimento e podem ser usados como resposta à incerteza do mercado. Esta tese é constituída por ensaios que suportam a aplicação dos modelos, e consiste num capítulo introdutório (designado por ensaio I) e mais seis ensaios sobre factores que discutem o uso de medidas de flexibilidade nas cadeias de abastecimento, em ambientes de incerteza, e um último ensaio sobre a extensão do conceito de flexibilidade ao tratamento da avaliação de planos de negócio. O segundo ensaio que apresentamos é sobre o valor do inventário num único estádio, enquanto medida de flexibilidade, sujeita ao crescente condicionalismo dos custos com posse de activos. Introduzimos uma nova classificação de artigos para suportar o indicador designado por overstock. No terceiro e quarto ensaio ampliamos a exploração do conceito de overstock, promovendo a interacção e o balanceamento entre vários estádios de uma cadeia de abastecimento, como forma de melhorar o desempenho global. Para sustentar a aplicação prática das abordagens, adaptamos o ensaio número três à gestão do desempenho, para suportar o estabelecimento de metas coordenadas e alinhadas; e adaptamos o quarto ensaio à coordenação das cadeias de abastecimento, como auxiliar ao planeamento integrado e sequencial dos níveis de inventário. No ensaio cinco analisamos o factor de produção “tecnologia”, em relação directa com a oferta de produtos de uma empresa, explorando o conceito de investimento, como medida de flexibilidade nas componentes de volume da procura e gama de produtos. Dedicamos o ensaio número seis à análise do factor de produção “Mão-de-Obra”, explorando as condicionantes para aumento do número de turnos na perspectiva económica e determinando o ponto crítico para a tomada de decisão em ambientes de incerteza. No ensaio número sete exploramos o conceito de internalização de operações, demarcando a nossa análise das demais pela definição do momento crítico que suporta a tomada de decisão em ambientes dinâmicos. Complementamos a análise com a introdução de factores temporais de perturbação, nomeadamente, o estádio de preparação necessário e anterior a uma eventual alteração de estratégia. Finalmente, no último ensaio, estendemos a análise da flexibilidade em ambientes de incerteza ao conceito de planos de negócio. Em concreto, exploramos a influência do número de pontos de decisão na flexibilidade de um plano, como resposta à crescente incerteza dos mercados. A título de exemplo, usamos o mecanismo de gestão sequencial do orçamento para suportar o nosso modelo. A crescente incerteza da procura obrigou a um aumento da agilidade e da flexibilidade das cadeias de abastecimento, limitando o uso de muitas das técnicas tradicionais de suporte à gestão, pela incapacidade de incorporarem os efeitos da incerteza. A flexibilidade é claramente uma vantagem competitiva das empresas que deve, por isso, ser quantificada. Com os modelos apresentados e com base nos resultados analisados, pretendemos demonstrar a utilidade da consideração da incerteza nos instrumentos de gestão, usando exemplos numéricos para suportar a aplicação dos modelos, o que claramente promove a aproximação dos desenvolvimentos aqui apresentados às práticas de negócio.

Cournot competition between a non-profit firm and a for-profit firm with uncertainty

In this paper, we consider a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analyze the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.

Implications of recent Australian wheat industry developments for overseas and domestic prices

This study is motivated by the proposition that the objectives of the AWB Ltd have changed since semi-privatisation of the Australian Wheat Board under the Wheat Marketing Act, 1989. Conceptualising this change of objectives as a shift from revenue maximization to profit maximization, this study examines the impact of such a change on the pricing policies of a multi-market price-setting firm. More specifically, this paper investigates, using two hypothetical objective functions, a risk averse AWB�s price-setting behaviour in an �overseas� and a �domestic� market in response to recent wheat industry developments. In the analysis these developments manifest themselves as differing price elasticities, differing transport costs and uncertain demand functions, and their implications particularly for the prices paid by domestic consumers are explored.

Planeamiento de la expansión de sistemas de transmisión considerando contingencias y demanda incierta

This paper presents a methodology and a mathematical model to solve the expansion planning problem that takes into account the effect of contingencies in the planning stage, and considers the demand as a stochastic variable within a specified range. In this way, it is possible to find a solution that minimizes the investment costs guarantying reliability and minimizing future load shedding. The mathematical model of the expansion planning can be represented by a mixed integer nonlinear programming problem. To solve this problem a specialized Genetic Algorithm combined with Linear Programming was implemented.

Cost Sharing under Uncertainty: An Algorithmic Approach to Cooperative Interval-Valued Games

Recently, Branzei, Dimitrov, and Tijs (2003) introduced cooperative interval-valued games. Among other insights, the notion of an interval core has been coined and proposed as a solution concept for interval-valued games. In this paper we will present a general mathematical programming algorithm which can be applied to find an element in the interval core. As an example, we discuss lot sizing with uncertain demand to provide an application for interval-valued games and to demonstrate how interval core elements can be computed. Also, we reveal that pitfalls exist if interval core elements are computed in a straightforward manner by considering the interval borders separately.

Fuzzy knowledge-based approach to treating uncertainty in inventory control

Inventory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).

Non-Stationary Demand in a Durable Goods Monopoly

In a context where demand for the services of a durable good changes over time, and this change may be uncertain, the paper shows that social welfare may be higher when the monopolist seller can commit to any future price level she wishes than when she cannot. Moreover, the equilibrium under a monopolist with commitment power may Pareto-dominate the equilibrium under a monopolist without commitment ability. These results affect the desired regulation of a durable goods monopolist in this context.

Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.