Vehicle routing problem (VRP) is a classic NP-hard optimization problem. It is generally accepted that an optimized routing scheme can cause huge difference in the cost in all stages of transportation. Consequently, t...
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Vehicle routing problem (VRP) is a classic NP-hard optimization problem. It is generally accepted that an optimized routing scheme can cause huge difference in the cost in all stages of transportation. Consequently, the VRP has evoked interest among the researchers of the field. Usually, a metaheuristic or an evolutionary algorithm is used for the solution of a VRP variant. In the last years, a number of swarm intelligence algorithms have been used for the solution of the problem. Initially, the two most classic swarm intelligence algorithms, the Ant Colony optimization and the Particle Swarm optimization, were used for the solution of this kind of problems. However, in the last years, more and more researchers solved the problem using a different swarm intelligence algorithm. In this paper, we focused in the presentation and analysis of the swarm intelligence algorithms that have been used for the solution of the problem. We give the advantages and disadvantages of each method, we focus in those ones that produced the best results in difficult VRPs and we present directions for the future of this kind of algorithms for the solution of a VRP variant.
Pumping stations scheduling for water supply systems can be optimized by the honey bees mating optimization algorithm (HBMOA). The study-case is the water distribution network of Oradea, Romania, consisting of 4 pumpi...
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Pumping stations scheduling for water supply systems can be optimized by the honey bees mating optimization algorithm (HBMOA). The study-case is the water distribution network of Oradea, Romania, consisting of 4 pumping stations, 3 tanks with variable water level and a constant level water source. The network was simplified, using a numerical network model and data recorded in August 2006, with two daily flow regimes (peak/off-peak). A modified form of HBMOA gave a suboptimal solution (the combination of pumps speed values), which is better, the daily pumping energy consumption being lower, than the one recorded in August 2006.
A simple hydropower optimization problem is used to compare the computational efficiency of the honey bees mating optimization algorithm (HBMOA), with the efficiency of other evolutionary algorithms, namely 3 recent o...
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ISBN:
(纸本)9781538639436
A simple hydropower optimization problem is used to compare the computational efficiency of the honey bees mating optimization algorithm (HBMOA), with the efficiency of other evolutionary algorithms, namely 3 recent ones: firefly algorithm, cuckoo search algorithm and bat-inspired algorithm (BA). The selected case study is a hydropower development on the Arges river, in Romania, consisting of Vidraru Reservoir (upstream) and Vidraru Hydro-Power Plant (downstream). Under specific conditions, Newton-Raphson method gives an accurate solution of the above optimization problem - that solution can be used as reference solution when assessing the computational efficiency of the above algorithms. From the overall performance viewpoint, BA is the most efficient algorithm, while from the hydropower viewpoint, HBMOA gives the preferred result: its annual energy production is the closest to the imposed reference value.
Pumping stations scheduling for water supply systems can be optimized by the honey bees mating optimization algorithm (HBMOA). The study-case is the water distribution network of Oradea, Romania, consisting of 4 pumpi...
详细信息
Pumping stations scheduling for water supply systems can be optimized by the honey bees mating optimization algorithm (HBMOA). The study-case is the water distribution network of Oradea, Romania, consisting of 4 pumping stations, 3 tanks with variable water level and a constant level water source. The network was simplified, using a numerical network model and data recorded in August 2006, with two daily flow regimes (peak/off-peak). A modified form of HBMOA gave a suboptimal solution (the combination of pumps speed values), which is better, the daily pumping energy consumption being lower, than the one recorded in August 2006.
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