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In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; retain the best selection so as to guard the diversity of group. Improved ordinal crossover...
In order to satisfy with the individual and various demand of customer, establish multi-type vehicles vehicle scheduling with picking-delivery model. According to the characteristics of model, hybrid genetic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; use the individual amount control choice strategy so as to guarantee...
In simplex hybrid genetic algorithm, widely using Nelder-Mead simplex method (NMSM) would lead to precocity of genetic algorithm and increase in computation quantity, so a novel simplex hybrid genetic algorithm is proposed in this paper. First, we propose a new efficient simplex crossover operator. Second, using the successful experiences of dividing the vertexes in NMSM into the best vertex, the...
This paper presents an unknown environment robot path planning algorithm. The robot working environments are expressed by grid model; Using digital potential field generated initial path population, and its optimization find the shortest path, and individual evaluation function were processed fitness function both feasible path and unfeasible path fitness function, and then by increasing the deleted...
No-wait flowshops with flowtime minimization are typical NP-complete combinatorial optimization problems, widely existing in practical manufacturing systems. Different from traditional methods by which objective of a new schedule being completely computed objective increment methods are presented in this paper by which the objective of an offspring being obtained just by objective increments and computational...
Assuming the market is efficient, an obvious portfolio management strategy is passive where the challenge is to track a certain benchmark like a stock index such that equal returns and risks are achieved. A tracking portfolio consists of a (usually small) weighted subset of stock funds. The weights are supposed to be positive here which means that short selling is not allowed. We investigate an approach...
In this paper we propose an improved hybrid genetic algorithm to overcome the deficiencies of the conventional algorithms in solving multi-modal function global optimization problems. The improved algorithm combines the niche genetic algorithm and steepest descent method: niche elimination operator is introduced to the algorithm to keep the diversity of the population and to ensure the search space...
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