The paper by Oscar H. Ibarra and Chul E. Kim studies heuristic algorithms for scheduling independent tasks on nonidentical processors. The authors analyze the worst-case behavior of several simple heuristic algorithms and present an $n \log n$ time-bounded algorithm for scheduling on two processors that achieves a finishing time of at most $(\sqrt{5} + 1)/2$ of the optimal finishing time. They also show that the problem of scheduling on identical processors with restricted task sets is P-complete, but the LPT (Last-In-First-Out) scheduling strategy yields schedules with a finishing time that approaches the optimal value as $n$ becomes large. The paper includes detailed analyses of the algorithms' run times and worst-case bounds, and provides examples to illustrate the theoretical results.The paper by Oscar H. Ibarra and Chul E. Kim studies heuristic algorithms for scheduling independent tasks on nonidentical processors. The authors analyze the worst-case behavior of several simple heuristic algorithms and present an $n \log n$ time-bounded algorithm for scheduling on two processors that achieves a finishing time of at most $(\sqrt{5} + 1)/2$ of the optimal finishing time. They also show that the problem of scheduling on identical processors with restricted task sets is P-complete, but the LPT (Last-In-First-Out) scheduling strategy yields schedules with a finishing time that approaches the optimal value as $n$ becomes large. The paper includes detailed analyses of the algorithms' run times and worst-case bounds, and provides examples to illustrate the theoretical results.