MEMINV: A hybrid efficient approximation method solving the multi skill-resource constrained project scheduling...

Area of Science:

• Operations Research
• Artificial Intelligence
• Computer Science

Background:

• The Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP) is a computationally challenging NP-Hard problem.
• Effective scheduling requires managing both resource availability and technical activity dependencies.

Purpose of the Study:

• To introduce MEMINV, a novel hybrid algorithm combining Memetic and Inverse methods.
• To address the complexities of the MS-RCPSP.

Main Methods:

• The MEMINV algorithm integrates the Memetic algorithm with the Inverse method.
• The Inverse method is employed to identify local optima.
• Population relocation is used to explore new solution spaces for enhanced evolutionary search.

Main Results:

• MEMINV was evaluated using the iMOPSE benchmark dataset.
• The proposed MEMINV algorithm demonstrated superior performance compared to existing methods.
• The algorithm generates optimized schedules for MS-RCPSP.

Conclusions:

• The MEMINV algorithm offers an effective solution for the MS-RCPSP.
• The generated schedules facilitate intelligent production planning in industrial settings.
• This approach presents a viable alternative to traditional manual planning methods.