Sharif Digital Repository

A multi-echelon supply chain design problem concerns the structure of the network and allocation of resources of the company to meet the demand forecast. This paper tries to design a multi-echelon supply chain network with five echelons including supplier, cross-dock, plant, distribution center and representative (customer). For this purpose, a mixed-integer mathematical model is developed to investigate the location of cross-docks, distribution centers, and also allocation between each pair of parties in order to minimize total cost of location and transportation. Due to the complexity of the model, a novel genetic algorithm is developed and applied on a real-world case study of Iran Khodro... 

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... 

Pharmaceutical drug Research and Development (R&D) outsourcing to contract research organizations (CROs) has experienced a significant growth in recent decades and the trend is expected to continue. A key question for CROs and firms in similar environments is which projects should be included in the firm's portfolio of projects. As a distinctive contribution to the literature this paper develops and evaluates a business support tool to help a CRO decide on clinical R&D project opportunities and revise its portfolio of R&D projects given the existing constraints, and financial and resource capabilities. A new mathematical programming model in the form of a capital budgeting problem is... 

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... 

Coordination of decentralized supply chains using contract design is a problem that has been widely addressed in the literature. We consider a divergent supply chain including a supplier and several retailers producing fashion products with short sale seasons. The retailers cooperate with the supplier as sales agents; i.e.; they work in the framework of revenue sharing contracts. Because of their proximity to the market, retailers can provide more accurate demand forecasts to the supplier that is used to decide on issues such as capacity building and market prices with regard to retailers stiff due dates, different lead times and different price-dependent demand functions. To ensure abundant... 

This paper presents mathematical modelling of joint lot sizing and scheduling problem in job shop environment under a set of working conditions. The main feature of the problem is to deal with flexible machines able to change their working speeds, known as process compressibility. Furthermore, produced items should be assembled together to make final products. In other words, the products have a multilevel structure, shown with bill of materials. As the problem is proved to be strongly NP-hard, it is solved by a memetic algorithm here. Computational experiences on the data of Mega Motor company are reported. Also, further experiences on random test data confirm the performance of the... 

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... 

In this study, we develop a bi-objective programming approach for due-date setting in make-to-order manufacturing with different classes of customers. We formulate the problem of quoting due-dates under the assumption that demand is dependent on lead-time and price is determined by the length of the delivery time. In addition, other parameters such as production policy, inventory holding, delivery system and capacity utilisation should be considered in due-date decisions. To this purpose, we consider additional objective function in traditional due-date management problem. So, the proposed bi-objective model attempts to maximise total profit and minimise rates of changes in capacity... 

Aircraft landing problem is to assign an airport's runways to the arrival aircrafts as well as to schedule the landing time of these aircrafts. In this paper, first a mixed integer goal programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design a hybrid meta-heuristic applying simulated annealing framework. The computational results show that the proposed algorithm can obtain the optimal solution for instances up to 100 aircrafts, and also it is capable of finding very high quality and comparable solutions for the problems with up to 500 aircrafts and 5 runways in a short time  

This study is dedicated to order penetration point (OPP) strategic decision making which is the boundary between make-to-order (MTO) and make-to-stock (MTS) policies. A multiproduct multiechelon production supply chain is considered where the first production stage manufactures semifinished products based on an MTS policy to supply the second production stage which operates on the MTO policy. The producer desires to find the optimal fraction of processing time fulfilled by supplier and optimal semifinished products buffer capacity in OPP. To calculate system performance indexes, the matrix geometric method is employed. Afterward, optimal solutions are obtained by enumeration and direct... 

This paper presents a novel model for designing a reliable network of facilities in closed-loop supply chain under uncertainty. For this purpose, a bi-objective mathematical programming formulation is developed which minimizes the total costs and the expected transportation costs after failures of facilities of a logistics network. To solve the model, a new hybrid solution methodology is introduced by combining robust optimization approach, queuing theory and fuzzy multi-objective programming. Computational experiments are provided for a number of test problems using a realistic network instance  

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... 

Time, cost and quality are among the crucial aspects of each project. In recent years, the demands of project stakeholders regarding reductions in the total cost and time of a project along with achieving the acceptable quality of the project have risen significantly. This leads researchers to developing models that incorporate the quality factor to previously existing time cost trade-off models.We develop a model for discrete time-cost-quality trade-off problem. For each activity, an execution mode can be selected from a number of possible ones. The time and cost of each mode are assumed to be crisp but the quality of each mode is a linguistic variable. Therefore, in this paper, fuzzy logic... 

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... 

In this paper, we develop an approach to optimally allocate a limited nonrenewable resource among the activities of a project, represented by a PERT-Type Network (PTN). The project needs to be completed within some specified due date. The objective is to maximize the probability of project completion on time. The duration of each activity is an arbitrary discrete random variable and also depends on the amount of consumable resource allocated to it. On the basis of the structure of networks, they are categorized as either reducible or irreducible. For each network structure, an analytical algorithm is presented. Through some examples, the algorithms are illustrated  

We consider coordination by contract in a divergent supply chain including one manufacturer and several retailers which produces fashion products with short sale seasons. The retailers cooperate with the manufacturer as sales agents; i.e., they work in the framework of revenue sharing contracts. Because of their proximity to the market, retailers can provide more accurate demand forecast for the manufacturer when he wants to decide on his capacity building (expansion), product assignment decision and market prices with regard to retailers stiff due date, different lead times and different price-dependent demand functions. To ensure abundant supply and increase their sales, the retailers have... 

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... 

Speed and price are the two most important factors in customer satisfaction and business success in today's competitive environment. Time-based product differentiation and segment pricing have provided firms with a great opportunity to profit enhancement. This paper presents a coding system for pricing/queuing models in the literature. In this article, a service/make-to-order firm with heterogeneous price and delivery time-sensitive customers as an M/M/1 queuing system is analyzed. The firm uses customers' heterogeneity to create market segments. Products offered to each segment differ only in price and delivery time. The objective of this profit-maximizing firm is to determine optimal...