The problem with the PO Logos company is that schedule for driver or bus still done manually which results in old operator determining who will depart. And distribution of driver's departure not evenly distributed so has just departed scheduled to leave again next day causes contact report this order get a replacement driver, because rules drivers at are once every three days. From these proble...

AGDISP (Aerial Spray Simulation Model) is used to predict the deposition of spray material released from an aircraft. Determining the optimal input values to AGDISP in order to produce a desired spray material deposition is extremely difficult (NP hard). SAGA, an intelligent optimization method based on the simple genetic algorithm, was developed to solve this problem. In this paper, we apply s...

Crossover operator is the predominant operator in most of Genetic Programming (GP) system. The empirical evidence shows that along with building blocks are constructed bigger and bigger as GP evolution proceeds, the crossover operator tends to disrupt those building blocks rather than preserve them. The traditional GP crossover primarily acts as macromutation. Looseness is used for representing...

being one of the major research fields in the robotics discipline, the robot motion planning problem deals with finding an obstacle-free start-to-goal path for a robot navigating among workspace obstacles. such a problem is also encountered in path planning of intelligent vehicles and automatic guided vehicles (agvs). traditional (exact) algorithms have failed to solve the problem effectively s...

We define an abstract normed vector space where the genetic operators are elements. This is used to define the disturbance of the generational operator G as the distance between the crossover and mutation operator (combined) and the identity. This quantity appears in a bound on the variance of fixed-point populations, and in a bound on the force //v - G(v)// that applies to the optimal populati...

In this paper, we present a novel triangulation heuristic and a new genetic algorithm to solve the problem of optimal tree decomposition of Bayesian networks. The heuristic, named MinFillWeight, aims to select variables minimizing the multiplication of the weights on nodes of fill-in edges. The genetic algorithm, named IDHGA, employs a new order-reserving crossover operator and a mutation opera...

This paper proposes a novel crowding method, which we call “Crowding with Asymmetric Crossover (CAX)” that can be applied to traditional 2-parent crossover operators. The Asymmetric Crossover operator begins with two parents. Then two offspring individuals are created, each offspring taking more characteristics from one of the two parents. This is an easy method to perform replacement between p...

To solve premature phenomenon and falling into local optimum of genetic algorithm, the simulated annealing algorithm is introduced to the genetic algorithm and a simulated annealing is presented based on genetic clustering algorithm, a new effective SA, crossover operator and mutation operator proposed for fitting the partition-based chromosome coding. In addition, the Euclidean distance is rep...

This paper first introduces the fundamental principles of immune algorithm (IA), greedy algorithm (GA) and delete-cross operator (DO). Based on these basic algorithms, a hybrid immune algorithm (HIA) is constructed to solve the traveling salesman problem (TSP). HIA employs GA to initialize the routes of TSP and utilizes DO to delete routes of crossover. With dynamic mutation operator (DMO) adop...

Most real-coded genetic algorithm research has focused on developing effective crossover operators, and as a result, many different types have been proposed. Some forms of crossover operators are more suitable to tackle certain problems than others, even at the different stages of the genetic process in the same problem. For this reason, techniques which combine multiple crossovers have been su...