Iranian Journal Of Operations Research
Volume:2 Issue: 1, Winter and Spring 2010

Multistage process monitoring has recently attracted notable attention in that thestatistical relationships between quality variables are taken into account. Here, we dealtwith the problem of monitoring and diagnosing a two-stage production process withattribute characteristics in which the outgoing quality variable is impacted by the incomingquality variable from the first process stage. Based on a sampling procedure which inspectseach n produced items, these attribute characteristics are assumed to follow binomial andPoisson distributions. Several monitoring techniques including a new method based on thegeneralized Poisson distribution are presented and the comparison is made to evaluate theeffectiveness of these procedures. Moreover, some fault diagnosis methods are fullyexplored in order to alleviate the identification of the process stage responsible for the outof-control conditions. The results of the simulation based studies reveal that a combined approach consisting of a proportion defective control chart and an adjusted control chart is quite efficacious in addressing the problems with regard to both the detection power and the fault diagnosis.

Most supplier selection models consider the buyer’s viewpoint and maximize only the buyer’s profit. This does not necessarily lead to an optimal situation for all the members of a supply chain. Coordination models have been developed to optimize the entire supply chain and align the decisions between its entities. Little research has been done on the application of these models in the supplier selection problem. Here, a combination of a supplier selection model and a co-ordination model in a centralized supply chain is considered. In the proposed model, the buyer selects the right supplier and order an appropriate quantity. The suppliers split the buyer ordered quantities into small lot sizes and deliver them over multiple periods. The objective function is to minimize the total cost of the supply chain. A nonlinear mathematical model is proposed for the problem. The total cost of the supply chain includes the costs of the buyer and the suppliers. The nonlinear model is transformed into a concave minimization problem and solved by considering the specific characteristics of the problem. Finally, the proposed model is illustrated by a numerical example.

The optimal harvesting policy is calculated as a function of the entering stock, the pricestate, the harvesting cost, and the rate of interest in the capital market. In order to determine the optimal harvest schedule, the growth function and stumpage price process are estimated for the Swedish mixed species forests. The stumpage price is assumed to follow a stochastic Markov process. A stochastic dynamic programming technique and traditional deterministic methods are used to obtain the optimal decisions. The expected present value of all future profits is maximized. The results of adaptive optimization are compared with results obtained by the traditional deterministic approach. The results show a significant increase in the expected economic values via optimal adaptive decisions.

We develop an algorithm for the solution of multiobjective linear plus fractionalprogramming problem (MOL+FPP) when some of the constraints are homogeneous innature. Using homogeneous constraints, first we construct a transformation matrix Twhich transforms the given problem into another MOL+FPP with fewer constraints. Then,a relationship between these two problems, ensuring that the solution of the originalproblem can be recovered from the solution of the transformed problem, is established.We repeat this process of transformation until all the homogeneous constraints areremoved. Then, we discuss the multi objective programming part, for which fuzzyprogramming methodology is proposed which works for the minimization of perpendiculardistances between two hyper planes (curves) at the optimal points of the objectivefunctions. A suitable membership function is defined with the help of the supremumperpendicular distance. A compromised optimal solution is obtained as a result of theminimization of the The supremum perpendicular distance. The corresponding optimalsolution to the original problem is obtained using the transformation matrix. Finally, anexample is given to illustrate the proposed model.

We suggest a method for finding the non-dominated points of the production possibilityset (PPS) with variable returns to scale (VRS) technology in data envelopment analysis(DEA). We present a multiobjective linear programming (MOLP) problem whose feasibleregion is the same as the PPS under variable returns to scale for generating non-dominated points. We demonstrate that Pareto solutions of the MOLP produce efficient units in DEA, and vice versa. We solve the MOLP problem by using a finite number of weights which are extreme rays of the cone generated by the efficient solutions. We obtain new efficient points by changing weights, and thus the efficient solutions set is produced.

Network and processing overhead associated with web services is a significant challenge toits performance. As a result, web service providers often announce a service level agreement.This ensures that consumers, who pay for the service, can get the service at a given quality level. In this paper, we study the competition between two providers offering functionally the same web services, where there is a monopoly service provider who offers a service that is complementary to their services. Each provider needs to decide a service level (L or H) he/she would offer and a corresponding price for the selected service level to meet the QoS guarantee. We combine modeling constructs from game theory and queuing theory to propose a model that can provide useful insights to service providers about pricing and general competitive strategies.

The fuzzy approach has undergone a profound structural transformation in the past fewdecades. Numerous studies have been undertaken to explain fuzzy approach for linear andnonlinear programs. While, the findings in earlier studies have been conflicting, recent studies of competitive situations indicate that fractional programming problem has a positive impact on comparative scenario. We propose one of the best interval approximations, close interval approximation of piecewise quadratic fuzzy numbers for solving fuzzy number fractional programming problem without converting it to a crisp problem. A new form of simplex method is introduced here for solving fuzzy number fractional programming problem using fuzzy arithmetic. The fuzzy analogue of some important theorems of fuzzy fractional programming problem proved. A fuzzy fractional programming problem is worked out as an example to illustrate the proposed method.