Hyperimmunoglobulin E (HIE) syndrome is a rare immunodeficiency disorder. HIE syndrome has multiple abnormalities include recurrent skin abscesses (hence, the name job syndrome), pneumonia, high serum levels of IgE, Facial, dental and skeletal features. We presented a case of HIE with dermatologic findings, recurrent productive cough and facial features. The diagnosis of HIE require differentiation from other disease. No definitive therapy is available for the treatment. The mainstay of treatment is the control of bacterial infections.

In this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un) availability is the same in all work centers. This study seems utterly new and it is applicable to any performance measure based on the completion time. The investigated models are very close to the actual scheduling problems, because they envisage the flexible job shop environments, heads, set-up times, arbitrary number of unavailability periods on all resources, arbitrary number of work-centers, any kind of cross-ability, any kind of resume-ability and several types of performance measures. The proposed model is presented to solve two-job problems because it is a graphical approach. However, it is concluded that the idea can be extended to n-dimensional problems as well.

In this paper, we study the common cycle multi-product lot-scheduling problem in a deterministic flexible job shop where all parameters (such as demand rates and setup times) are deterministic and constant over an infinite planning horizon. This production facility involves several work centers (production stages) where each stage has one or more parallel identical machines. A product requires a sequence of operations in different stages based on its unique process route. Moreover, each product must be processed by at most one machine at each stage, but some products may skip some stages. The objective is minimizing the sum of setup and inventory holding costs per time unit without backlogging. This problem involves a combinatorial part (assignment of products to machines at each work center and their sequencing on each machine), and a continuous part (lot-sizing and production starting time for each product at each stage). A new mixed zero-one nonlinear program has been developed whose optimal solution determines simultaneously the optimal assignment of products to machines at each stage, the optimal sequence on each machine, the optimal lot sizes and the optimal beginning times for each production run. In order to reduce computational complexity, instead of solving this MINLP directly, we propose an efficient heuristic method to determine near optimal solution for this model. Two other applicable cases (Zero setup costs and Lot streaming) are also studied and required modifications in the model formulation and the solution procedure are described. Moreover, an example has been presented to illustrate the applicability of the proposed model.