Sharif Digital Repository

Pricing and availability of tickets have always been a source of confusion for customers in transportation industries. What is the best time to buy tickets? Why passengers taking the same flight might pay significantly different prices for the same seat? Why round trip tickets between two cities sometimes become cheaper than the one-way flights between them? Is it fair to buy a ticket for an itinerary cheaper than a ticket for just a part of it? These observations make customers wonder why they pay higher prices for shorter flights. In this paper, we study the airlines' revenue management systems and explain some of these pricing schemes in travel industries. We develop a simulator to study... 

We propose a robust optimization framework to deal with uncertain component reliabilities in redundancy allocation problems in series-parallel systems. The proposed models are based on linearized versions of standard mixed integer nonlinear programming (MINLP) formulations of these problems. We extend the linearized models to address uncertainty by assuming that the component reliabilities belong to a budgeted uncertainty set, and develop robust counterpart models. A key challenge is that, because the models involve nonlinear functions of the uncertain data, classical robust optimization approaches cannot apply directly to construct their robust optimization counterparts. We exploit problem... 

In this article, we address the multiple-night stay hotel revenue management. Using a decomposition method, we transform the multiple-night stay revenue management into a single night. To this end, we define effective arrival rate for each night that is derived from all the booking requests that contain the night, excluding the possible 'customer losses'. A customer is labeled 'loss' either because of the existence of an expensive night in his itinerary or because of a stock-out occurrence over his stay. We calculate the probabilities of these two incidents and then update the effective daily arrival rate, accordingly. In this way, we can use the classical single-night revenue management,... 

One concern of many investors is to own the assets which can be liquidated easily. Thus, in this paper, we incorporate portfolio liquidity in our proposed model. Liquidity is measured by an index called turnover rate. Since the return of an asset is uncertain, we present it as a trapezoidal fuzzy number and its turnover rate is measured by fuzzy credibility theory. The desired portfolio turnover rate is controlled through a fuzzy chance constraint. Furthermore, to manage the portfolios with asymmetric investment return, other than mean and variance, we also utilize the third central moment, the skewness of portfolio return. In fact, we propose a fuzzy portfolio mean-variance-skewness model... 

We propose a robust deviation framework to deal with uncertain component reliabilities in the constrained redundancy optimization problem (CROP) in series-parallel reliability systems. The proposed model is based on a linearized binary version of standard nonlinear integer programming formulations of this problem. We extend the linearized model to address uncertainty by assuming that the component reliabilities belong to an interval uncertainty set, where only upper and lower bounds are known for each component reliability, and develop a Min-Max regret model to handle data uncertainty. A key challenge is that, because the deterministic model involves nonlinear functions of the uncertain... 

The objective of this research is to develop a practical research and development (R&D) portfolio selection model that addresses the effective R&D project valuation issue, while tackling R&D uncertainty in portfolio optimization. Fuzzy set theory is employed to capture and model the uncertain project information. To evade the well-known complexities of fuzzy real option valuation, the recently developed fuzzy pay-off method is used to more effectively valuate R&D projects. The resulting problem is formulated as a fuzzy zero-one integer programming model that handles uncertainty of input data in order to determine the optimal portfolio. Two satisfaction measures, which are based on... 

The aim of this paper is to develop a practical R&D portfolio selection model that addresses effective R&D project valuation issue, while it tackles R&D uncertainty in portfolio optimization. Fuzzy sets theory is employed to capture and model the inaccuracy in project information. To avoid the well-known complications of fuzzy real option valuation, the fuzzy pay-off method is used to more effectively value R&D projects. The resulting problem is formulated as a fuzzy zero-one integer programming model which is later transformed into a crisp mathematical formulation to solve the problem for various degrees of risk. A numerical example is used to illustrate the proposed approach  

This paper is concerned with the study of the constant due-date assignment policy in repetitive projects, where the activity durations are exponentially distributed random variables. It is then extended to the case where activity durations follow generalized Erlang distributions. The main feature of this research over the classical PERT networks is that the projects are generated according to a renewal process and share the same facilities. Our approach is first to obtain the project completion time distribution, for each generated project, by constructing a proper continuous-time Markov chain, and then to compute the optimal constant lead time for each particular project. The repetitive... 

In this paper, three critical issues with the paper "A fuzzy set approach for R&D portfolio selection using a real options valuation model", coauthored by Wang and Hwang and published in Omega 2007 are addressed. Shortcomings of the original work are highlighted and corrective measures to improve the approach are proposed  

Make-to-order firms use different strategies, such as dynamic pricing and due date management, to influence their performance. In these strategies, orders are segmented into classes based on their sensitivity to lead time and price. Quoting different prices and lead times to different classes of customer can increase a firm's profit and its capacity utilization. Most research in this area does not consider the effects of production constraints on price and lead time decisions. In this paper, we consider the role of flexibility in dynamically choosing the price, lead time and segmentation of customers in make-to-order environments with limited production capacity and multi-period horizon... 

A study was conducted to select the best alternative for the development of construction panels as well as investment in its manufacturing in Iran. Three alternatives are considered, cement-bonded wood composite product, substituted products (such as concrete panel) sandwich panel and a mixture of them. We apply the analytic network process (ANP) to achieve this goal. A hierarchy is designed to prioritize benefits, opportunities, costs and risks (BOCR) by using the Analytic Hierarchy Process (AHP) ratings approach. To evaluate the "control criteria" of the system, a control hierarchy is also created and prioritized by applying the Analytic Network Process (ANP). A total of four major control... 

This paper deals with decision making in a remanufacturing facility where returned products arrive according to a Poisson process. Arrivals have different routings among the facility stations since they have different defects and need different operations. A returned product is either accepted for remanufacturing or sold at a salvage value without working on it in order to reduce congestion. The authors provide an analytical model using a queuing network theory to obtain the best policy for accepting returned products. Furthermore, a continuous genetic algorithm is implemented to solve the model, which happens to be a mixed integer nonlinear programming problem. Several examples are solved... 

This paper studies simultaneous lot sizing and scheduling problem in a job shop environment over a finite number of periods. The machines are flexible such that the production manager is able to change their working speeds. Also, the production schedule of the items over machines should be in consistence with technological precedence relationships. The problem is formulated as an integer linear program. Then, a number of valid inequalities are developed based on the problem structures. The proposed valid inequalities are added to the problem formulation in a "cut and branch" manner to accelerate the search process by common solvers. Finally, performance of the valid inequalities is... 

In this research, a novel approach is developed to predict stocks return and risks. In this three stage method, through a comprehensive investigation all possible features which can be effective on stocks risk and return are identified. Then, in the next stage risk and return are predicted by applying data mining techniques for the given features. Finally, we develop a hybrid algorithm, on the basis of filter and function-based clustering; the important features in risk and return prediction are selected then risk and return re-predicted. The results show that the proposed hybrid model is a proper tool for effective feature selection and these features are good indicators for the prediction... 

Revenue management (RM) and customer relationship management (CRM) are the standard strategies of many hotels to increase their profitability. Although the objectives and time horizons of RM and CRM are different, they can be considered as complimentary business strategies. However, the integration has received little attention both practically and theoretically. In this study, we develop an approach to jointly make the capacity allocation and overbooking decisions considering CRM strategies over a hotel network. Hotel customers are divided based on their lifetime value into two major groups of occasional and loyal customers. Price discounts and room availability guarantee (RAG) are offered... 

We develop heuristic procedures for concurrent design of block layout, material flow network, and input and output stations. Unlike the common practice in the flexible bay structure layout design, our objective function includes both loaded and empty flow between pairs of I/O stations. This measure of effectiveness is the main determinant of the fleet size of the vehicles, which in turn is the major driver of the total investment and operational costs in vehicle-based material handling. Our work is the first to design flexible bay structure layouts for loop-based material flow patterns. We first develop heuristic algorithms to configure the layout on the foundations of a unidirectional loop... 

Existing revenue management methods and heuristics rely on specific demand-side assumptions such as customers' independent decisions over time. We relax the assumption that purchasing decisions depend only on the current price and are independent of previous prices of the same or similar products. On the contrary, we assume that customers' decisions depend on the product's past prices through a reference price. With this new dimension, a firm needs not only to manage its remaining capacity but also to control the reference price to maximize its expected future profit. In this situation, we show that some of the main analytical properties such as monotonicity or modularity of the firm's value... 

This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and especially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which could be applicable to multiple uncertainties conditions. Thus, in our approach, the half-length of these intervals is also represented by... 

Network marketing is a business model that depends upon a network of distributors for growth, such as in multilevel marketing. A direct selling method features independent agents that make up a distribution network for goods and services. This paper provides a framework to study the network marketing by adopting the traditional channel. To motivate all distributers in network marketing as well as retailers, it is required to design a well-balanced distribution and pricing system. The allocated commission for distributers in different layers of network marketing is part of pricing system, which is vital. In this paper, we develop an approach to determine all elements of system, including... 

Optimal queuing system design includes deciding about some variables such as location, capacity, price, and delivery time. In order to develop an optimized system, it is essential to solve the optimization problem for all the decision variables simultaneously. In this paper, a make-to-order system is considered. In this system, some facilities are developed in different points. According to the make-to-order system definition, these facilities keep no inventory from final product. Orders are received from customers and the requested products are assembled. Due to existence of some differences among customers, they are divided into two distinct categories including express and regular...