Multi-group ant colony algorithm based on simulated annealing method

To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed.

Solving flexible job shop scheduling problem by a multi-swarm collaborative genetic algorithm

The flexible job shop scheduling problem(FJSP),which is NP-hard,widely exists in many manufacturing industries.It is very hard to be solved.A multi-swarm collaborative genetic algorithm(MSCGA)based on the collaborative optimization algorithm is proposed for the FJSP.Multi-population structure is used to independently evolve two sub-problems of the FJSP in the MSCGA.Good operators are adopted and designed to ensure this algorithm to achieve a good performance.Some famous FJSP benchmarks are chosen to evaluate the effectiveness of the MSCGA.The adaptability and superiority of the proposed method are demonstrated by comparing with other reported algorithms.

A Multi-pipe Path Planning by Modified Ant Colony Optimization

Path planning in 3D geometry space is used to find an optimal path in the restricted environment, according to a certain evaluation criteria. To solve the problem of long searching time and slow solving speed in 3D path planning, a modified ant colony optimization is proposed in this paper. Firstly, the grid method for environment modeling is adopted. Heuristic information is connected with the planning space. A semi-iterative global pheromone update mechanism is proposed. Secondly, the optimal ants mutate the paths to improve the diversity of the algorithm after a defined iterative number. Thirdly, co-evolutionary algorithm is used. Finally, the simulation result shows the effectiveness of the proposed algorithm in solving the problem of 3D pipe path planning.

Maintaining an Optimal Flow of Forest Products under a Carbon Market: Approximating a Pareto Set of Optimal Silvicultural Regimes for Eucalyptus fastigata

A competitive co-evolutionary Multi-Objective Genetic Algorithm (cc-MOGA) was used to approximate a Pareto front of efficient silvicultural regimes for Eucalyptus fastigata. The three objectives to be maximised included, sawlog, pulpwood and carbon sequestration payment. Three carbon price scenarios (3CPS), i.e. NZ $25, NZ $50 and NZ $100 for a tonne of CO2 sequestered, were used to assess the impact on silvicultural regimes, against a fourth non-carbon Pareto set of efficient regimes (nonCPS), determined from a cc-MOGA with two objectives, i.e. competing sawlog and pulpwood productions. Carbon prices included in stand valuation were found to influence the silvicultural regimes by increasing the rotation length and lowering the final crop number before clearfell. However, there were no significant changes in the frequency, timing, and intensity of thinning operations amongst all the four Pareto sets of solutions. However, the 3CPS were not significantly different from each other, which meant that these silvicultural regimes were insensitive to the price of carbon. This was because maximising carbon sequestration was directly related to the biological growth rate. As such an optimal mix of frequency, intensity, and timing of thinning maintained maximum growth rate for as long as possible for any one rotation.