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Showing 3 results for Aghaie
Etebari, Aaghaie, Khoshalhan,
Volume 3, Issue 1 (4-2012)
Abstract
In recent years, enriching traditional revenue management models by considering the customer choice behavior has been a main challenge for researchers. The terminology for the airline application is used as representative of the problem. A popular and an efficient model considering these behaviors is choice-based deterministic linear programming (CDLP). This model assumes that each customer belongs to a segment, which is characterized by a consideration set, which is a subset of the products provided by the firm that a customer views as options. Initial models consider a market segmentation, in which each customer belongs to one specific segment. In this case, the segments are defined by disjoint consideration sets of products. Recent models consider the extension of the CDLP to the general case of overlapping segments. The main difficulty, from a computational standpoint, in this approach is solving the CDLP efficiently by column generation. Indeed, it turns out that the column generation subproblem is difficult on its own. It has been shown that for the case of nonoverlapping segments, this can be done in polynomial time. For the more general case of overlapping segments, the column generation sub-problem is NP-hard for which greedy heuristics are proposed for computing approximate solutions. Here, we present a new approach to solve this problem by using a genetic algorithm and compare it with the column generation method. We comparatively investigate the effect of using the new approach for firm’s revenue
Samimi, Aghaie, Shahriari,
Volume 3, Issue 2 (9-2012)
Abstract
We deal
with the relationship termination problem in the context of individual-level customer
relationship management (CRM) and use a Markov decision process to determine
the most appropriate occasion for termination of the relationship with a
seemingly unprofitable customer. As a particular case, the
beta-geometric/beta-binomial model is considered as the basis to define
customer behavior and it is explained how to compute customer lifetime value
when one needs to take account of the firm’s choice as to whether to continue
or terminate relationship with unprofitable customers. By numerical examples provided
by simulation, it is shown how a stochastic dynamic programming approach can be
adopted in order to obtain a more precise estimation of the customer lifetime
value as a key criterion for resource allocation in CRM.
Morovatdar, Aghaie, Roghanian, Asl Haddad,
Volume 4, Issue 1 (5-2013)
Abstract
We consider criticality in project networks having imprecise activity duration times. It is well known that finding all possibly critical paths of an imprecise project network is an NP-hard problem. Here, based on a method for finding critical paths of crisp networks by using only the forward recursion of critical path method, for the first time an algorithm is proposed which can find all possibly critical paths of interval-valued project networks. The proposed algorithm considers interactivity among paths which has not been yet considered in the fuzzy project scheduling literature. The extension of the proposed algorithm to the fuzzy network calculates criticality degrees of activities and paths of projects without any need to enumerate all project paths. Although algorithms for calculating criticality degrees in fuzzy networks have been previously proposed, despite the fact that they mostly consider a specific type of fuzzy numbers as activity duration times, the exiting algorithms do not discriminate possibly critical paths before calculating the criticality degrees. The computational experience on a series of well-known project samples confirms the algorithm to be remarkably more efficient than similar algorithms for fuzzy networks.
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