No abstract

No abstract

The multi-item single level capacitated dynamic lot-sizing problem consists of scheduling N items over a horizon of T periods. The objective is to minimize the sum of setup and inventory holding costs over the horizon subject to a constraint on total capacity in each period. No backlogging is allowed. Only one machine is available with a fixed capacity in each period. In case of a single item production, an optimal solution algorithm exists. But for multi-item problems, optimal solution algorithms are not available. It has been proved that even the two-item problem with constant capacity is NP-hard, that is, it is in a class of problems that are extremely difficult to solve in a reasonable amount of time. This has called for searching good heuristic solutions. For a multi-item problem, it would be more realistic to consider the setup time, since switching the machine from one item to another would require a setup time. This setup time would be independent of item sequences and this could be a very important parameter from practical point of view. The current research work has been directed toward the development of a model for multiitem problem considering this parameter. Based on the model a program has been executed and feasible solutions with some real life data have been obtained.

In order to achieve the therapeutic purpose, the choice of the most suitable delivery route is of indisputable importance. Therefore, certain factors must be taken into consideration when delivering a active substance, namely its own properties, the disease to be diagnosed and the desired beneficial time. The active substances can be directly to the target tissue or organ or can be delivered by systemic routes.

No abstract