ElsevierGuijarro Tarradellas, E.; Cardós, M.; Babiloni, E. (2012). On the exact calculation of the fill rate in a periodic review inventory policy under discrete demand patterns. European Journal of Operational Research. 218(2): 442-447. doi:10.1016/j.ejor.2011.11.025. On the exact calculation of the fill rate in a periodic review inventory policy under discrete demand patterns GUIJARRO, E., CARDÓS, M., BABILONI, E. Universidad Politécnica de Valencia AbstractThe primary goal of this paper is the development of a generalized method to compute the fill rate for any discrete demand distribution in a periodic review policy. The fill rate is defined as the fraction of demand that is satisfied directly from shelf. In the majority of related work, this service metric is computed by using what is known as the traditional approximation, which calculates the fill rate as the complement of the quotient between the expected unfulfilled demand and the expected demand per replenishment cycle, instead of focusing on the expected fraction of fulfilled demand. This paper shows the systematic underestimation of the fill rate when the traditional approximation is used, and revises both the foundations of the traditional approach and the definition of fill rate itself. As a result, this paper presents the following main contributions: (i) a new exact procedure to compute the traditional approximation for any discrete demand distribution; (ii) a more suitable definition of the fill rate in order to ignore those cycles without demand; and (iii) a new standard procedure to compute the fill rate that outperforms previous approaches, especially when the probability of zero demand is substantial. This paper focuses on the traditional periodic review, order up to level system under any uncorrelated, discrete and stationary demand pattern for the lost sales scenario.Keywords: inventory, fill rate, periodic review, discrete demand, lost sales. 2 Introduction and literature reviewOne of the service measures most commonly used in practice is the volume fill rate, defined as the fraction of demand that is immediately fulfilled from on hand stock (see Silver et al. (1998) or Axsäter (2000) among others). Therefore, in practice it also indicates the size of the backordering demand when this is allowed (Tempelmeier (2007)). The volume fill rate is also known as item fill rate, unit fill rate or just fill rate (denoted by β in the rest of this paper).Over the last sixty years, several works have suggested methods to estimate the fill rate in different contexts. However, to the best of our knowledge, there is not any exact and general method to estimate it under any discrete demand context. This paper focuses on the exact estimation of the fill rate for the periodic review, order up to level (base stock) system. This stock policy is commonly denoted by (R, S) and consists of examining the status of an item every R fixed time periods and launching a replenishment order which raises the inventory position to the order up to level S.Traditionally ...

Public administrations are organizations whose mission is to serve the interests of society by providing efficient and sustainable services. Much of the information received from public administrations uses social media due to their versatility and capacity to reach a large number of citizens. Among them, Twitter is the most widely used, especially to disseminate messages with a high social content. This type of messages falls within the discipline of social marketing. However, when public administrations use Twitter for social marketing communication, it is not known which factors are the most decisive to achieve the social objective for which they are issued. This article provides an answer to this question, using the Analytic Network Process Multicriteria method to determine which factors matter and how they are interrelated when issuing social marketing messages through Twitter. The result of this research reveals that from the 22 factors analyzed, the most influential from a social marketing point of view are the average age of population, the existence of a strategic communication plan, the number of tweets and the average number of tweets per day, the number of followers, retweets and mentions, as well as the efficiency of the account.

This paper considers the bi-criteria scheduling problem of simultaneously minimising the total completion time and the number of tardy jobs with release dates on a single machine. Since the problem had been classified as NP-Hard, two heuristics (HR9 and HR10) were proposed for solving this problem. Performance evaluations of the proposed heuristics and selected solution methods (HR7 and BB) from the literature were carried out on 1,100 randomly generated problems ranging from 3 to 500 jobs. Experiment results show that HR7 outperformed HR10 when the number of jobs (n) is less than 30, while HR10 outperformed HR7 for n≥ 30. OPSOMMINGIn hierdie artikel word die bi-kriteria-skeduleringsprobleem bestudeer waar die totale voltooiingstyd en die aantal take wat laat is op 'n enkele masjien geminimiseer moet word. Verskeie heuristieke word voorgestel en getoets om sodoende die beste benadering te identifiseer.

This paper focuses on computing on-hand stock levels at the beginning of a replenishment cycle for a lost sales inventory system with periodic reviews and discrete demand. A base-stock policy is used for replenishments. The literature provides an Exact method which requires a huge computational effort, and two closed-form approximate methods that arise from the backordering case, the Non-stockout and the Bijvank&Johansen. In this paper we propose three new and closed-form approaches that explicitly consider the lost sales assumptions:the Adjusted Non-stockout, the Polar Opposite and the 1-Step methods. Existing and proposed methods are evaluated in terms of their accuracy when computing the cycle service level and the fill rate. In this sense, results show that the Bijvank&Johansen and 1-Step methods provide similar performance but present different behaviours in terms of under or over estimating service measures that have different implications on the design of stock policies.

With the adoption of a service-oriented paradigm on the Web, many software services are likely to fulfil similar functional needs of the end-users. We propose in this paper to aggregate functionally equivalent software services within one single virtual service, that is an association of a functionality, a graphical user interface (GUI), and a set of selection rules. When an end-user invokes such virtual service through its GUI to answer his/her functional need, the software service that better answer to the end-user selection policy is selected and executed, and the result is then rendered to the end-user through the GUI of the virtual service. A key innovation in this paper is the flexibility of the service selection policy we propose. First, each selection policy can refer to heterogeneous parameters (e.g. service price, end-user location, and QoS). Second, additional parameters can be added to an existing or new policy with little investment. Third, it is the enduser who defines which selection policy to apply during the selection process, thanks to the GUI element added as part of the virtual service design. This approach has been validated by designing, implementing, and testing an end-to-end architecture, including the implementation of several virtual services, and considering several software services available today in the Web.