Algorithms

An algorithm can be defined as a sequence of operations tailored to solve a specific problem.

We usually measure the performance of an algorithm by its time complexity during runtime.

Terminology

• Heuristic: give a quick solution for a specific problem, but it's usually not optimal
• Metaheuristic: general heuristics methods that can be applied to multiple different problems.
  Examples: Simulated Annealing
• Greedy algorithm: select the best result at each iteration, so the global optimum is obtained by repeatedly selecting the local optimum.
  Examples: Nearest Neighbour, Kruskal, Prim, Dijkstra

Flow

• Permutation Flow Shop: product chain with operation sequence fixed
  • https://wikipedia.org/wiki/Flow-shop_scheduling
• Job Shop: product chain with operation sequence variable
  • https://wikipedia.org/wiki/Job_shop

Resources

• List of algorithms – Wikipedia
• Algorithm and data structure visualization – David Galles
• Michael Sambol – Youtube Channel