目的针对当前物流背景下普遍出现的送货公司外包、退换货频繁等问题,结合现有的碳排放政策,提出低碳背景下开放式同时送取货选址−路径模型(Low-Carbon Open Location-routing Problem with Simultaneous Pickup and Delivery Problem,LO...目的针对当前物流背景下普遍出现的送货公司外包、退换货频繁等问题,结合现有的碳排放政策,提出低碳背景下开放式同时送取货选址−路径模型(Low-Carbon Open Location-routing Problem with Simultaneous Pickup and Delivery Problem,LOLRPSPD),并通过改进野马算法进行求解。方法首先设计一种新的解码方式,使得原离散问题可以采用连续算法求解。之后,运用哈尔顿序列生成初始解,改进非线性进化概率因子,使用模拟二进制交叉,增加变异操作,以及精英保留、设置连续失败重新初始化等步骤,改进野马算法。最后,通过6组不同大小的算例将改进野马算法与原始野马算法、模拟退火算法、粒子群算法、遗传算法进行对比。结果针对中大型算例,改进野马算法远超原始野马算法。针对小型算例,在确保准确率的同时,改进野马算法对比各经典算法也在速度上具有优势。结论提出的LOLRPSD模型具备合理性,改进的野马算法针对选址路径问题具有较好的搜索能力。展开更多
Bird swarm algorithm(BSA), a novel bio-inspired algorithm, has good performance in solving numerical optimization problems. In this paper, a new improved bird swarm algorithm is conducted to solve unconstrained optimi...Bird swarm algorithm(BSA), a novel bio-inspired algorithm, has good performance in solving numerical optimization problems. In this paper, a new improved bird swarm algorithm is conducted to solve unconstrained optimization problems. To enhance the performance of BSA, handling boundary constraints are applied to fix the candidate solutions that are out of boundary or on the boundary in iterations, which can boost the diversity of the swarm to avoid the premature problem. On the other hand, we accelerate the foraging behavior by adjusting the cognitive and social components the sin cosine coefficients. Simulation results and comparison based on sixty benchmark functions demonstrate that the improved BSA has superior performance over the BSA in terms of almost all functions.展开更多
Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of p...Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of pas- sengers at the current stop and at the following stops is con- structed and a new heuristic algorithm, shuffled complex evo- lution method developed at the University of Arizona （SCE- UA）, is adopted to optimize the holding times of early buses. Results show that the improved holding strategy can provide better performance compared with a traditional schedule- based holding strategy and no-control strategy. The compu- tational results are also evidence of the feasibility of using SCE-UA in optimizing the holding times of early buses at a stop.展开更多
文摘目的针对当前物流背景下普遍出现的送货公司外包、退换货频繁等问题,结合现有的碳排放政策,提出低碳背景下开放式同时送取货选址−路径模型(Low-Carbon Open Location-routing Problem with Simultaneous Pickup and Delivery Problem,LOLRPSPD),并通过改进野马算法进行求解。方法首先设计一种新的解码方式,使得原离散问题可以采用连续算法求解。之后,运用哈尔顿序列生成初始解,改进非线性进化概率因子,使用模拟二进制交叉,增加变异操作,以及精英保留、设置连续失败重新初始化等步骤,改进野马算法。最后,通过6组不同大小的算例将改进野马算法与原始野马算法、模拟退火算法、粒子群算法、遗传算法进行对比。结果针对中大型算例,改进野马算法远超原始野马算法。针对小型算例,在确保准确率的同时,改进野马算法对比各经典算法也在速度上具有优势。结论提出的LOLRPSD模型具备合理性,改进的野马算法针对选址路径问题具有较好的搜索能力。
基金Supported by the National Natural Science Foundation of China(11871383,71471140 and 11771058)
文摘Bird swarm algorithm(BSA), a novel bio-inspired algorithm, has good performance in solving numerical optimization problems. In this paper, a new improved bird swarm algorithm is conducted to solve unconstrained optimization problems. To enhance the performance of BSA, handling boundary constraints are applied to fix the candidate solutions that are out of boundary or on the boundary in iterations, which can boost the diversity of the swarm to avoid the premature problem. On the other hand, we accelerate the foraging behavior by adjusting the cognitive and social components the sin cosine coefficients. Simulation results and comparison based on sixty benchmark functions demonstrate that the improved BSA has superior performance over the BSA in terms of almost all functions.
文摘Holding strategies are among the most commonly used operation control strategies. This paper presents an improved holding strategy. In the strategy, a mathematical model aiming to minimize the total waiting times of pas- sengers at the current stop and at the following stops is con- structed and a new heuristic algorithm, shuffled complex evo- lution method developed at the University of Arizona （SCE- UA）, is adopted to optimize the holding times of early buses. Results show that the improved holding strategy can provide better performance compared with a traditional schedule- based holding strategy and no-control strategy. The compu- tational results are also evidence of the feasibility of using SCE-UA in optimizing the holding times of early buses at a stop.
