关键词: 智能感知网, 物料配送, 动态优化, 禁忌搜索, 改进蚁群算法

Abstract: Aiming at the demands for accurate and timely material delivery in dynamic workshop environment, intelligent sensing devices are deployed to build a real-time sensing network. According to the sensed real-time production state, delivery time windows of workstations are adjusted dynamically. The material delivery dynamic optimization model based on intelligent sensing network is set up with the minimum material delivery cost as the optimization goal. An improved tabu-search-based Ant Colony Optimization（ACO） algorithm is designed to solve the problem. To improve the search rate and stability, the algorithm merges the memory function of tabu search into ACO. The 2-opt local optimization method and the maximum-minimum pheromone strategy are introduced. A case study is conducted to verify the feasibility and effectiveness of the proposed model and algorithm.

Key words: intelligent sensing network, material delivery, dynamic optimization, tabu search, improved ACO algorithm