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Abstract Background Many countries, such as Niger, are considering changing their vaccine vial size presentation and may want to evaluate the subsequent impact on their supply chains, the series of steps required to get vaccines from their manufacturers to patients. The measles vaccine is particularly important in Niger, a country prone to measles outbreaks. Methods We developed a detailed discrete event simulation model of the vaccine supply chain representing every vaccine, storage location, refrigerator, freezer, and transport device (e.g., cold trucks, 4 × 4 trucks, and vaccine carriers) in the Niger Expanded Programme on Immunization (EPI). Experiments simulated the impact of replacing the 10-dose measles vial size with 5-dose, 2-dose and 1-dose vial sizes. Results Switching from the 10-dose to the 5-dose, 2-dose and 1-dose vial sizes decreased the average availability of EPI vaccines for arriving patients from 83% to 82%, 81% and 78%, respectively for a 100% target population size. The switches also changed transport vehicle's utilization from a mean of 58% (range: 4-164%) to means of 59% (range: 4-164%), 62% (range: 4-175%), and 67% (range: 5-192%), respectively, between the regional and district stores, and from a mean of 160% (range: 83-300%) to means of 161% (range: 82-322%), 175% (range: 78-344%), and 198% (range: 88-402%), respectively, between the district to integrated health centres (IHC). The switch also changed district level storage utilization from a mean of 65% to means of 64%, 66% and 68% (range for all scenarios: 3-100%). Finally, accounting for vaccine administration, wastage, and disposal, replacing the 10-dose vial with the 5 or 1-dose vials would increase the cost per immunized patient from $0.47US to $0.71US and $1.26US, respectively. Conclusions The switch from the 10-dose measles vaccines to smaller vial sizes could overwhelm the capacities of many storage facilities and transport vehicles as well as increase the cost per vaccinated child.

Maximizing the rate at which Radio Frequency IDentification (RFID) tags can be read is a critical issue for end-users of RFTD technology as well as for RFID hardware manufacturers. Supply chain applications typically involve tags for which the reader-tag communication is regulated by a protocol that enforces a slotted Aloha scheme. This article shows how to dynamically adjust the parameter of this scheme as a function of the number of tags remaining and the last-used value of the parameter, such that the total amount of time required to read a given set of tags is minimized. To do so, several variations of this stochastic shortest path problem are formulated as Markov decision processes, which are then solved for the optimal policies by exploiting the models' decomposability. Computational results indicate that the optimal policies are complex and static heuristics perform poorly but that a myopic heuristic performs nearly optimally under the current cost structure when the reader processes all slots before selecting a new parameter value. Keywords: Markov decision process, slotted Aloha, myopic heuristic, Gen-2, 1. Background and motivation Radio Frequency IDentification (RFID) is a wireless technology for automatic identification in which a reader emits a series of commands to extract data/information from tags. We [...]

A remnant inventory distribution system is considered where a set of geographically dispersed distribution centers meet stochastic demand for a one-dimensional product. This demand arises from some other set of geographically dispersed locations. The product is replenished at the centers in a limited number of standard sizes, while the demand is for various smaller sizes of the product and arrives over time according to a Poisson process. There are costs associated with cutting and transportation and scrap can be profitably reclaimed. The combined production (cutting) and distribution problem is modeled as a network. A linear programming formulation is solved for a deterministic version of this problem using mean demand rates and the optimal dual multipliers are used to assign inherent values to remnants of various sizes. These values are then used to develop a price-directed policy that can be used in a stochastic environment. A simulation study shows that this policy significantly outperforms heuristic policies from the literature as well as other heuristic policies that have been used in the steel industry for a similar problem. Theoretical insights into the structure of the proposed optimization problem are provided along with proofs of several important results. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix] Keywords: Remnant inventory, cutting stock problem, supply chain management, 1. Introduction We consider a supply chain problem that combines elements of several classical optimization problems, including the cutting stock problem, inventory management and distribution. Relatively large pieces, called raws, [...]

A minimum cost, system-based component test plan for assessing the reliability of a series system with n different components, having their respective unknown failure rates, is presented. The test plan uses type-II censoring which compared a predetermined number of failures for each component with the total time-on-test. Data generated by the test plan are then cross-referenced with a decision rule for accepting or rejecting the entire system.

In most low‐ and middle‐income countries supported by the World Health Organization's Expanded Program on Immunization, vaccines are distributed through a legacy medical supply chain that is typically not cost‐efficient. Vaccines require storage and transport in a temperature‐controlled environment; this requires a "cold" distribution chain with capacity constraints on cold storage and cold transport. We propose an approach to redesigning the vaccine distribution chain that includes locating a set of intermediate distribution centers (DCs) and determining the flow paths from the central store (where vaccines are received into a country) through one or more of these to health clinics where vaccination actually occurs. In addition, the transport vehicles to allocate to each flow path, and the cold storage devices to use at each clinic or intermediate DC are determined. The redesigned network does not have to follow the current four‐tiered, arborescent structure commonly found in practice, but can use alternative network structures. To redesign this network optimally, we develop a mixed‐integer programming (MIP) model that can be used for small‐to‐medium‐sized problems and also present a hybrid heuristic–MIP method to obtain good solutions for larger problems. Numerical results are shown using data reflecting distribution networks in several countries in sub‐Saharan Africa. [ABSTRACT FROM AUTHOR]

The dual of a geometric programming problem with negative degree of difficulty is often infeasible. It has been suggested that such problems be solved by finding a dual |approximate, solut which minimizes a measure of the infeasibility, e.g., the summed squares of the infeasibilities in t constraints. We point out the shortcomings in that approach, and suggest a simple technique to ensur dual feasibility, namely the addition of a constant term to the primal objective., A simple procedure can be adopted to ensure dual feasibility in geometric programming problems with negative difficulty levels. A constant term is added to the primal objective to gain dual feasibility, with the dual in such programming problems usually considered infeasible. The level of infeasibility could be reduced by identifying an approximate dual solution, although there are shortcomings to this procedure. The restricting behaviour of the primal variables is determined by the dual feasible solution.

A generalized linear program to solve the primal optimum without the need to determine the subsidiary problems is described. The algorithm is an alternative to the dual-based procedure in solving geometric programming problems. Analysis shows that the linearized form provides information in all posynomials including those with slack constraints. In addition, optimal primal-dual relationships yield information on the multiple optima characterizing the primal under those conditions.

We study an (R, s, S) inventory control policy with stochastic demand, lost sales, zero lead‐time and a target service level to be satisfied. The system is modeled as a discrete time Markov chain for which we present a novel approach to derive exact closed‐form solutions for the limiting distribution of the on‐hand inventory level at the end of a review period, given the reorder level (s) and order‐up‐to level (S). We then establish a relationship between the limiting distributions for adjacent values of the reorder point that is used in an efficient recursive algorithm to determine the optimal parameter values of the (R, s, S) replenishment policy. The algorithm is easy to implement and entails less effort than solving the steady‐state equations for the corresponding Markov model. Point‐of‐use hospital inventory systems share the essential characteristics of the inventory system we model, and a case study using real data from such a system shows that with our approach, optimal policies with significant savings in inventory management effort are easily obtained for a large family of items. [ABSTRACT FROM AUTHOR]

We examine the problem seneduling jobs at a bank of parallel identical machines where each job requires either a major or a minor setup depending on the job that was processed immediately before it. Several heuristic procedures are proposed and tested with respect to makespan, average flowtime and time spent on setups. [ABSTRACT FROM AUTHOR]

We describe a simple modification of Palmer's heuristic for scheduling jobs in a flow shop. While the additional computation required is relatively small, the performance of the algorithm compares very well with that of the more sophisticated and better algorithm of Campbell, et al. (1970) at a fraction of the effort required by the latter. [ABSTRACT FROM AUTHOR]

Within immunization programs supported by the World Health Organization, current practice is to use a vial as the basic unit for managing vaccine inventories at the clinic level. In addition to being inconvenient, this has the potential to induce errors in the ordering process. We propose alternative ordering policies based on using inner pack quantities corresponding to secondary vaccine packaging and draw upon visual management, simplified inventory tracking, better housekeeping, and other lean related concepts that have been used in the manufacturing sector to simplify and improve the vaccine inventory management system. We present analyses that show that the proposed polices only require very modest increases in fixed storage and transport requirements. [ABSTRACT FROM PUBLISHER]

Research into the methods used by cable television networks to promote viewership of programs is presented. A quantitative model which enables the network to use the process of promotion to efficiently manage its advertising contracts is presented.

In many developing countries, inefficiencies in the supply chain for the World Health Organization's Expanded Program on Immunization (EPI) vaccines are of grave concern; these inefficiencies result in thousands of people not being fully immunized and creates significant risk of disease epidemics. Thus, there is a great deal of interest in these countries in building tools to analyze and optimize how vaccines flow down several levels of the supply chain from manufacturers to vaccine recipients. This article develops a mathematical model for typical vaccine distribution networks in developing countries. This model has been successfully adapted for supply chains in three different countries (Niger, Thailand, and Vietnam), and its application to several issues of interest to public health administrators in developing countries is discussed. [ABSTRACT FROM PUBLISHER]

Many vaccines are manufactured in large, multi-dose vials that once opened, must be used within a matter of hours. As a result, clinicians (especially those in remote locations) face difficult tradeoffs between opening a vial to satisfy a potentially small immediate demand versus retaining the vial to satisfy a potentially large future demand. This article formulates a Markov decision process model that determines when to conserve vials as a function of time of day, the current vial inventory, and the remaining clinic-days until the next replenishment. The objective is to minimize open-vial waste while administering as many vaccinations as possible. It is analytically established that the optimal policy is of a threshold type. Furthermore, an extensive sensitivity analysis is conducted that speaks to the benefits of consolidating demand, investing in buffer stock, and adopting different vial sizes. Lastly, a practical heuristic is evaluated and shown to perform competitively with the optimal policy. [ABSTRACT FROM PUBLISHER]