  We consider the Pm || Cmax scheduling problem where the goal is to schedule n
jobs on m identical parallel machines to minimize makespan. We revisit the
famous Longest Processing Time (LPT) rule proposed by Graham in 1969. LPT
requires to sort jobs in non-ascending order of processing times and then to
assign one job at a time to the machine whose load is smallest so far. We
provide new insights on LPT and discuss the approximation ratio of a
modification of LPT that improves Graham's bound from 4/3 - 1/(3m) to 4/3 -
1/(3(m-1)) for m >= 3 and from 7/6 to 9/8 for m = 2. We use Linear Programming
(LP) to analyze the approximation ratio of our approach. This performance
analysis can be seen as a valid alternative to formal proofs based on
analytical derivation. Also, we derive from the proposed approach an O(n log n)
heuristic. The heuristic splits the sorted jobset in tuples of m consecutive
jobs (1,...,m; m+1,...,2m; etc.) and sorts the tuples in non-increasing order
of the difference (slack) between largest job and smallest job in the tuple.
Then, List Scheduling is applied to the set of sorted tuples. This approach
strongly outperforms LPT on benchmark literature instances.
