An Optimization Method for Enterprise Resource Integration Based on Improved Particle Swarm Optimization

Area of Science:

• Operations Research
• Management Science
• Computational Intelligence

Background:

• Enterprise growth relies on efficient resource integration and optimization.
• Firms face challenges with limited resources and simultaneous, multi-goal activities.
• Effective resource scheduling is crucial for project success and cost reduction.

Purpose of the Study:

• To investigate an ideal resource integration strategy for enhancing project completion efficiency and reducing enterprise expenses.
• To develop a method for properly integrating and scheduling limited enterprise resources while achieving multiple objectives.
• To propose and evaluate an enhanced particle swarm optimization (IPSO) technique for internal resource integration.

Main Methods:

• Incorporation of chaos theory (logistic mapping) into particle population initialization to ensure even particle dispersion and high quality.
• Development of a dynamic inertia weight update strategy based on fitness value to improve convergence speed and global search capability in later stages.
• Creation of a fitness function specifically tailored to task completion time for evaluating resource integration solutions.

Main Results:

• The proposed IPSO method effectively addresses issues of uneven particle dispersion and slow convergence common in traditional particle swarm optimization (PSO).
• IPSO demonstrates improved convergence speed and a higher likelihood of finding the global optimal solution.
• Experimental results on an enterprise resource integration case confirm IPSO's ability to swiftly locate optimal solutions.

Conclusions:

• The enhanced particle swarm optimization (IPSO) technique provides an effective solution for enterprise resource integration and optimization.
• IPSO enables achieving the shortest job completion time and minimizing costs.
• This approach offers a valuable tool for improving overall enterprise efficiency and competitiveness.