CAJ | 학술논문

为了提高集装箱港口泊位-岸桥分配效果和优化效率，以集卡运距和船舶在港时间最小为优化目标，建立了多目标离散泊位-岸桥分配模型，利用混沌云粒子群算法对泊位-岸桥分配模型进行求解，开发了粒子可行-整数化处理模块，内嵌于混沌云粒子群算法进化中，制定了粒子编码规则，设计了多目标函数的粒子历史极值和全局极值的计算方法，提出了基于混沌云粒子群优化算法求解多目标离散泊位-岸桥分配模型的新方法，数值算例结果证明了该模型和算法的可行性和实用性。
위료제고집장상항구박위-안교분배효과화우화효솔，이집잡운거화선박재항시간최소위우화목표，건립료다목표리산박위-안교분배모형，이용혼돈운입자군산법대박위-안교분배모형진행구해，개발료입자가행-정수화처리모괴，내감우혼돈운입자군산법진화중，제정료입자편마규칙，설계료다목표함수적입자역사겁치화전국겁치적계산방법，제출료기우혼돈운입자군우화산법구해다목표리산박위-안교분배모형적신방법，수치산례결과증명료해모형화산법적가행성화실용성。
To improve allocation effectiveness and optimize efficiency of the berth and quay-crane in container terminal, a multi-objective berth and quay-crane allocation mode is established, so as to minimize the transportation distance of container truck and stay time of ships in terminal, and the Chaos Cloud Particle Swarm Optimization (CCPSO) algorithm is used to solve the new model. The feasible-integer processing module for particles is designed, and embedded in the CCPSO algorithm. Devising the rules of particles encoding and calculation method of the historical extremum and the global extremum of particles, a new multi-objective berth and quay-crane allocation mode optimized by the CCPSO algorithm is proposed. Numerical example result shows that the proposed model and algorithm has certain the practicability and effectiveness.