CAJ | 학술논문

交通拥堵问题的加剧使传统物流网络在我国大型城市已达到极限，未来地面物流系统将逐步向地下不同层次里转移并释放出城市地上空间．本文以斯坦纳最小树（SMT）为理论模型，建立了符合我国大型城市不断扩展这一特点的树状地下物流网络布局模型．由于SMT为NP一完全问题，因此算法的寻优能力是研究的关键．本文所采用的模拟植物生长算法（PGSA）是以植物向光性理论为启发式准则的智能算法，该算法是利用人工植物在给定物流节点集解空间中的生长过程得到城市地下物流网络的最优布局．通过对国际公布的STEINLIB实例数据计算并与蚁群算法和模拟退火算法进行比较，表明模拟植物生长算法具有较强的精确性、稳定性和全局搜索能力．
교통옹도문제적가극사전통물류망락재아국대형성시이체도겁한，미래지면물류계통장축보향지하불동층차리전이병석방출성시지상공간．본문이사탄납최소수（SMT）위이론모형，건립료부합아국대형성시불단확전저일특점적수상지하물류망락포국모형．유우SMT위NP일완전문제，인차산법적심우능력시연구적관건．본문소채용적모의식물생장산법（PGSA）시이식물향광성이론위계발식준칙적지능산법，해산법시이용인공식물재급정물류절점집해공간중적생장과정득도성시지하물류망락적최우포국．통과대국제공포적STEINLIB실례수거계산병여의군산법화모의퇴화산법진행비교，표명모의식물생장산법구유교강적정학성、은정성화전국수색능력．
With the aggravation of traffic jam traditional logistics network has reached high-point in big cities in China, so the logistics system on the ground will gradually transfer to underground on various layers in the future so as to release the ground space in cities. Based on SMT theory, this paper establishes underground tree logistics network layout model. Because SMT is NP-complete problem, the algorithm optimization capability is the key of research. Plant growth simulation algorithm （PGSA） in this paper is an intelligence optimization algorithm, which takes plant phototropism growth pattern as its heuristic criterion. Through artificial plant growth process in solution space of given logistics node set, we can get the optimal layout of underground logistics network in cities. Through the calculation of STEINLIB lab data announced internationally, PGSA is demonstrated with better accuracy, stability and global searching ability, by comparing the solutions of ant algorithm and simulated annealing algorithm.