Sentence examples for assignment setup from inspiring English sources

The objective of this model was the selection of locations for distribution centers, identification of transportation assignment, setup of inventory policy according to the servicing needs, and scheduling the routes of the vehicle to meet the customer demands.

In this package, we define the optimal design as a sample assignment setup that minimizes our objective function based on principle of least square method [ 13].

The default algorithm (implemented in function optimal.shuffle) sought to first block all variables considered to generate a single initial assignment setup, then identify the optimal one which minimizes the objective functions (i.e., the one with most homogeneous cross-batch strata distribution) through shuffling the initial setup.

The default algorithm implemented in OSAT will first block three variables considered (i.e., SampleType, Race and AgeGrp) to generate a single initial assignment setup, and then identify the optimal one with most homogeneous cross-batch strata distribution through shuffling the initial setup.

In the alternative algorithm, multiple (typically thousands of or more) sample assignment setups are first generated by procedure described in the block randomization step above, based only on the list of specified blocking variable(s).

It works by first blocking SampleType only to generate a pool of assignment setups, and then select the optimal one with most homogeneous cross-batch strata (i.e., SampleType, Race and AgeGrp) distribution.

The alternative algorithm (implemented in function optimal.blcok) sought to first block specified variables (e.g., list of variables of primary interests) to generate a pool of assignment setups, then select the optimal one which minimize the objective functions based on all variables considered (including those variables which are not included in the block randomization step).

Hence, the common assignment of setup costs and times to individual products appears to be questionable since setup costs are often caused by changing the basic processing mode and not for switching between different product types.

First, the usual assignment of setup costs and times to products does not realistically reflect the changeover processes prevalent in advanced manufacturing technology.

The assignment of setup families to blocks is modelled by use of binary decision variables and determined by the optimization model based on the size and timing of demand and capacity considerations.

Given the assignment of products to setup families, fixed setup sequences of products within a family are defined based on human expertise and technological requirements.