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GA BinPacking MATLAB
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Bin packing problem
In the bin packing problem, objects of different volumes must be packed into a finite number of bins or containers each of volume V in a way that minimizes the number of bins used. In computational complexity theory, it is a combinatorial NP-hard problem.
There are many variations of this problem, such as 2D packing, linear packing, packing by weight, packing by cost, and so on. They have many applications, such as filling up containers, loading trucks with weight capacity constraints, creating file backups in removable media and technology mapping in Field-programmable gate array semiconductor chip design.
The bin packing problem can also be seen as a special case of the cutting stock problem. When the number of bins is restricted to 1 and each item is characterised by both a volume and a value, the problem of maximising the value of items that can fit in the bin is known as the knapsack problem.
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ABC Algorithms MATLAB
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ABC algorithm Matlab GUI test with many subordinate and tag functions. Artificial bee colony (ABC) algorithm artificial bee colony (ABC) is one of the most recently defined algorithms by Dervis karaboga in 2005, inspired by the intelligent behavior of bees. It is simple, particle swarm optimization (PSO) and differential evolution (DE) algorithms, and uses unique common control parameters such as ant colony size and maximum number of cycles. ABC, as an optimization tool, provides a population-based search process called food which individual positions are modified with time for Apis mellifera, which aims to discover high nectar content with food sources and the last place with the highest nectar. In ABC system, artificial bees fly around the multidimensional search space and some (hired and bystander bees) choose food sources for themselves and their nest mates, experience and adjust their positions. Some (scouts) fly and randomly choose food sources without using experience. If a new source has more nectar than the previous one in their memory, remembering a new location, they forget the previous one. Therefore, ABC system combines the local search method, carried out by employing bystander bees, with the global search method, and managed by the onlooker scouts, trying to balance the exploration and development process. Since 2005, the research group of intelligent systems, headed by D. karaboga, has studied ABC algorithm, real world problems and their applications. Karaboga and bashtirk's version of ABC unconstrained numerical optimization algorithm problem and constrained optimization problem and its extended version.
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