This article studies the amortized efficiency of the "move-to-front" and similar rules for dynamically maintaining a linear list. It shows that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules, assuming that accessing the ith element from the front of the list takes Θ(i) time. Other heuristics like transpose and frequency count do not share this property. The results are generalized to show that move-to-front is within a constant factor of optimum as long as the access cost is a convex function. The article also studies paging, where access cost is not convex. The paging rule corresponding to move-to-front is the "least recently used" (LRU) replacement rule. It analyzes the amortized complexity of LRU, showing that its efficiency differs from the offline paging rule (Belady's MIN algorithm) by a factor depending on the size of fast memory. No online paging algorithm has better amortized performance. The article discusses the amortized complexity of self-organizing lists, showing that move-to-front is approximately optimal under certain conditions. It proves that move-to-front is within a constant factor of optimal for any sequence of operations, including offline algorithms. The results are generalized to convex access costs and applied to paging, where LRU and FIFO perform within a constant factor of the optimal algorithm. The article concludes that amortized complexity provides a more robust and realistic measure of algorithmic efficiency than average-case analysis.This article studies the amortized efficiency of the "move-to-front" and similar rules for dynamically maintaining a linear list. It shows that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules, assuming that accessing the ith element from the front of the list takes Θ(i) time. Other heuristics like transpose and frequency count do not share this property. The results are generalized to show that move-to-front is within a constant factor of optimum as long as the access cost is a convex function. The article also studies paging, where access cost is not convex. The paging rule corresponding to move-to-front is the "least recently used" (LRU) replacement rule. It analyzes the amortized complexity of LRU, showing that its efficiency differs from the offline paging rule (Belady's MIN algorithm) by a factor depending on the size of fast memory. No online paging algorithm has better amortized performance. The article discusses the amortized complexity of self-organizing lists, showing that move-to-front is approximately optimal under certain conditions. It proves that move-to-front is within a constant factor of optimal for any sequence of operations, including offline algorithms. The results are generalized to convex access costs and applied to paging, where LRU and FIFO perform within a constant factor of the optimal algorithm. The article concludes that amortized complexity provides a more robust and realistic measure of algorithmic efficiency than average-case analysis.