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The total cost objective function is constructed by summing the variable production costs and the fixed setup costs. Variable costs are calculated by multiplying the unit variable cost of each machine by the number of units produced on that machine ($X_i$).

Conditions: There are multiple machines with distinct variable and fixed costs.; $X_i$ represents the continuous production quantity on machine $i$.; $Y_i$ represents the binary activation status of machine $i$.; The goal is cost minimization.

The total cost objective function is constructed by summing the variable production costs and the fixed setup costs. Variable costs are calculated by multiplying the unit variable cost of each machine by the number of units produced on that machine ($X_i$).

Conditions: There are multiple machines with distinct variable and fixed costs.; $X_i$ represents the continuous production quantity on machine $i$.; $Y_i$ represents the binary activation status of machine $i$.; The goal is cost minimization.

In Least Cost Branch and Bound, the algorithm selects the node with the minimum cost from the available nodes to explore next. This prioritizes paths that appear most promising based on the current cost evaluation.

Conditions: Applicable when using the Least Cost strategy for Branch and Bound.; A cost function is defined for the problem.

In Least Cost Branch and Bound, the algorithm selects the node with the minimum cost from the available nodes to explore next. This prioritizes paths that appear most promising based on the current cost evaluation.

Conditions: Applicable when using the Least Cost strategy for Branch and Bound.; A cost function is defined for the problem.