Scheduling optimization method for multi-mode resource-constrained projects using two-stage genetic algorithm

Abstract

The invention discloses a multi-mode resource-constrained project scheduling optimization method using a two-stage genetic algorithm, which comprises the following steps: obtaining information required for scheduling; judging whether there is a feasible solution; preprocessing; calculating task level values; Population; evolves in two stages: Stage 1 adopts hierarchical-based scheduling sequence crossover mutation operation and generates a list of individual execution modes based on the earliest completion time of the task and calculates its fitness value, so that the algorithm quickly converges to the vicinity of the optimal solution, stage 2 Adopt the execution mode and scheduling sequence list crossover mutation operation and use the FBI&D method to improve the population to calculate the fitness value, carry out the expansion search of the neighborhood to find the optimal solution; output the scheduling optimization result; compared with the single-stage search strategy, the present invention has higher efficiency Search efficiency and optimization capabilities.

Description

technical field [0001] The invention relates to the fields of computer technology, information technology and system engineering, in particular to a scheduling optimization method for a multi-mode resource-constrained project, more specifically, to a multi-mode resource-constrained project scheduling optimization using a two-stage genetic algorithm method. Background technique [0002] Resource-Constrained Project SchedulingProblem RCPSP (Resource-Constrained Project SchedulingProblem) refers to how to scientifically and reasonably allocate resources, arrange the execution sequence of tasks to determine their start and completion times under the constraints of the time-series relationship between resources and tasks, so as to achieve established goals such as : Optimization of construction period, cost, etc. With more and more modern enterprises adopting a project-oriented organizational structure and management model, RCPSP has a strong engineering background and is widely...

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Problems solved by technology

[0004] In order to overcome the long calculation time of existing accurate algorithms, which cannot be applied to large-scale problems, the incompleteness of the search space of heuristic algorithms and semi-intelligent algorithms combined with heuristics and the efficiency of intelligent algorithms depend on the design of the algorithm itself and the type of problem, etc. Insufficient, the present invention provides a kind of multimodal resource-constrained project scheduling optimization method using two-stage genetic algorithm, which effectively reduces the solution time of the resource-constrained project scheduling problem and improves the solution quality

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