Abstract
In real industrial engineering, job shop scheduling problem (JSSP) is considered to be one of the most difficult and tricky non-deterministic polynomial-time (NP)-hard problems. This study proposes a new hybrid heuristic algorithm for solving JSSP inspired by the tissue-like membrane system. The framework of the proposed algorithm incorporates improved genetic algorithms (GA), modified rumor particle swarm optimization (PSO), and fine-grained local search methods (LSM). To effectively alleviate the premature convergence of GA, the improved GA uses adaptive crossover and mutation probabilities. Taking into account the improvement of the diversity of the population, the rumor PSO is discretized to interactively optimize the population. In addition, a local search operator incorporating critical path recognition is designed to enhance the local search ability of the population. Experiment with 24 benchmark instances show that the proposed algorithm outperforms other latest comparative algorithms, and hybrid optimization strategies that complement each other in performance can better break through the original limitations of the single meta-heuristic method.
Highlights
Solve Job Shop Scheduling Problem.The production scheduling system plays a vital role in a specialized manufacturing system
The cell-like membrane system studies the computer theory of a single cell, while the tissue-like membrane system explores the mechanism by which multiple cells freely placed in the same environment cooperate and communicate with each other to complete calculations
By introducing a real-coded ascending mapping method, rumor particle swarm optimization (PSO) can be effectively applied to the Job shop scheduling problem (JSSP) which belongs to the discrete combinatorial optimization problem
Summary
As a classic discrete combinatorial optimization problem, JSSP has its inherent stubborn nature Whether it is classic GA or PSO, a single meta-heuristic method will always face the problem of premature convergence, and its search performance has reached its limit. Considering the above statement, this work presented a hybrid heuristic algorithm inspired by tissue-like membrane system for solving the JSSP. A new hybrid heuristic algorithm inspired by tissue-like membrane system is proposed for JSSP. Aiming at the results of the above optimization, an algorithm for quickly identifying critical paths is presented Based on this algorithm, a local search strategy is given.
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