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When the number of bins is restricted to 1 and each item is characterized by both a volume and a value, the problem of maximizing the value of items that can fit in the bin is known as the knapsack problem. A variant of bin packing that occurs in practice is when items can share space when packed into a bin.
The number of bins used by this algorithm is no more than twice the optimal number of bins. In other words, it is impossible for 2 bins to be at most half full because such a possibility implies that at some point, exactly one bin was at most half full and a new one was opened to accommodate an item of size at most B / 2 {\displaystyle B/2} .
Therefore, all FF bins except at most one have sum at least 2/3, and the number of FF bins is at most 2+OPT/(2/3) = 3/2*OPT+1. The "problematic" items are those with size larger than 1/2. So, to improve the analysis, let's give every item larger than 1/2 a bonus of R. Define the weight of an item as its size plus its bonus.
First-fit-decreasing (FFD) is an algorithm for bin packing.Its input is a list of items of different sizes. Its output is a packing - a partition of the items into bins of fixed capacity, such that the sum of sizes of items in each bin is at most the capacity.
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Initialize an empty bin and call it the "open bin". For each item in order, check if it can fit into the open bin: If it fits, then place the new item into it. Otherwise, close the current bin, open a new bin, and put the current item inside it. In short: NFD orders the items by descending size, and then calls next-fit bin packing.
High-multiplicity bin packing is a special case of the bin packing problem, in which the number of different item-sizes is small, while the number of items with each size is large. While the general bin-packing problem is NP-hard , the high-multiplicity setting can be solved in polynomial time, assuming that the number of different sizes is a ...
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related to: number of bins excel formula practice exercises list