Models for Location Inventory Routing Problem of Cold Chain Logistics with NSGA-Ⅱ Algorithm

In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location,inventory and transportation.Due to the complex of LIR problem( LIRP), a multi-objective genetic algorithm(GA), non-dominated sorting in genetic algorithm Ⅱ( NSGA-Ⅱ) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-Ⅱ provides a competitive performance than GA,which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem.

Study on the Inventory Routing Problem of Refined Oil Distribution Based on Working Time Equilibrium

Taking the distribution route optimization of refined oil as background, this paper studies the inventory routing problem of refined oil distribution based on working time equilibrium. In consideration of the constraints of vehicle capacity, time window for unloading oil, service time and demand of each gas station, we take the working time equilibrium of each vehicle as goal and establish an integer programming model for the vehicle routing problem of refined oil distribution, the objective function of the model is to minimize the maximum working time of vehicles. To solve this model, a Lingo program was written and a heuristic algorithm was designed. We further use the random generation method to produce an example with 10 gas stations. The local optimal solution and approximate optimal solution are obtained by using Lingo software and heuristic algorithm respectively. By comparing the approximate optimal solution obtained by heuristic algorithm with the local optimal solution obtained by Lingo software, the feasibility of the model and the effectiveness of the heuristic algorithm are verified. The results of this paper provide a theoretical basis for the scheduling department to formulate the oil distribution plan.

Competitive analysis of online inventory problem with interrelated prices

This paper investigates the online inventory problem with interrelated prices in which a decision of when and how much to replenish must be made in an online fashion even without concrete knowledge of future prices. Four new online models with different price corre- lations are proposed in this paper, which are the linear-decrease model, the log-decrease model, the logarithmic model and the exponential model. For the first two models, the online algo- rithms are developed, and as the performance measure of online algorithm, the upper and lower bounds of competitive ratios of the algorithms are derived respectively. For the exponential and logarithmic models, the online algorithms are proposed by the solution of linear programming and the corresponding competitive ratios are analyzed, respectively. Additionally, the algorithm designed for the exponential model is optimal, and the algorithm for the logarithmic model is optimal only under some certain conditions. Moreover, some numerical examples illustrate that the algorithms based on the dprice-conservative strategy are more suitable when the purchase price fluctuates relatively flat.

Competitive analysis of price online inventory problem with cost function

In this paper,a new price is given to the online decision maker at the beginning of each day.The trader must decide how many items to purchase according to the current price.We present three variants and an online algorithm based on cost function.The competitive ratio of the online algorithm is given for each variant,which is a performance measure of an online algorithm.More importantly,we show that the online algorithm is optimal.

Mathematical Modelling for a Multi-Product Inventory Routing Problem with Split Delivery

In this article, a multi-product inventory routing problem is studied. One-depot and many retailers in a finite time period are considered, and split delivery is allowed as well for the addressed problem. The objective is to minimize the overall cost including vehicle cost, inventory holding cost and transportation cost while the delivery schedule and the quantity of each product for each retailer have to be decided simultaneously. A mathematical model is presented for solving the addressed optimally and example is illustrated as well.

不孕(育)症夫妻二元应对异质性研究及相关因素分析

目的·采用潜在剖面分析法探索辅助生殖技术(assisted reproductive technology,ART)治疗前不孕(育)症夫妻二元应对水平的潜在剖面,并探讨不同剖面间的差异及相关因素。方法·招募2023年9月至11月在上海交通大学医学院附属仁济医院生殖医学中心接受ART治疗的不孕(育)症初诊夫妇,应用一般资料问卷、生育压力量表(Fertility Problem Inventory,FPI)、二元应对评估工具(Dyadic Coping Inventory,DCI)、生育生活质量量表(Fertility Quality of Life Tool,FertiQoL量表)进行评估。采用潜在剖面分析探索不孕(育)症夫妻治疗前二元应对的剖面类型,比较不同剖面之间的一般特征,及FPI和FertiQoL量表得分;采用多元Logistic回归分析不同二元应对剖面的相关因素。结果·共纳入257对不孕(育)症夫妻,女性平均年龄(30.15±3.07)岁,男性平均年龄(31.82±3.82)岁,平均婚龄(3.75±2.16)年,平均不孕(2.90±1.92)年;男方导致不孕118对、女方导致不孕109对、男女共患不孕(育)症30对;男性DCI平均得分(128.25±19.15)分,女性(129.91±18.32)分。根据二元应对水平,257对夫妻可分为4个潜在剖面:共同积极组(153对,59.5%)、共同消极组(85对,33.1%)、男方积极组(12对,4.7%)及男方消极组(7对,2.7%);不同剖面不孕(育)症夫妻的年龄、FPI得分、FertiQoL量表得分、再婚比例间差异均具有统计学意义(均P<0.05)。多元Logistic回归分析结果显示,以共同积极组为参照,共同消极组的男方年龄更大(OR=1.122,95%CI 1.004~1.254,P=0.036)、男女双方FPI得分更高(男:OR=1.019,95%CI 1.003~1.035,P=0.018;女:OR=1.020,95%CI 1.004~1.036,P=0.015)、男方FertiQoL量表得分更低(OR=0.966,95%CI 0.937~0.996,P=0.029)。结论·接受ART治疗前不孕(育)症夫妻的二元应对水平可分为4个剖面类型;与共同积极应对夫妻相比,男性生育压力大、年龄大、感知的生育生活质量低,以及女性生育压力大均是夫妻共同消极应对的危险因素。

基于样本划分的数据驱动报童问题研究

大数据时代的到来为企业库存管理带来了前所未有的机遇,同时也对其相应的决策方法提出了新的挑战。高效利用实时市场数据支撑库存管理智能决策已经成为企业提升库存管理效率的关键。传统库存管理研究是基于需求预测的基础上再做库存决策。而近年来流行的数据驱动库存管理方法是跳过需求预测的过程,直接建立需求数据与库存决策的关系。本文研究数据驱动的经典报童问题,其随机需求分布是未知的,报童只有若干期历史的需求数据。本文基于数据样本划分提出了新的数据驱动鲁棒优化方法来解决报童的订货问题。该方法通过将需求数据样本划分成不同的区间来构造随机需求分布的模糊集,从而求解相应的鲁棒优化问题。理论证明了该方法随着样本量的增加,其解收敛于最优解。数值实验表明相对已有的鲁棒方法,新方法具有相对弱的鲁棒性,但平均性能更好,并且计算复杂度相对小很多。同时表明本文提出的样本划分鲁棒方法比SAA等数据驱动方法具有更好的平均性能和更强的鲁棒性。

行为运营管理研究综述

经理人的决策质量对于实现高效运营管理至关重要。然而,在商业实践中,经理人的决策过程常常伴随着非理性行为,并最终导致决策偏差。决策偏差是企业无法实现高效管理的根本问题,其成因广泛、机理深邃,治理困难,因此面临着重大的研究挑战。近年来,学术界针对运营管理中的各种场景,尤其是库存和供应链管理,进行了一系列研究。这些研究广泛识别了不同类型的决策偏差,并反复检验了这些偏差的稳健性,探索了决策偏差的形成机制和干预治理方法。然而,现有的研究视角广泛,方向零散,缺乏对决策偏差的系统性认知和梳理。因此,本文系统性地讨论库存与供应链管理中的决策者行为偏差问题,分析其科学内涵和形成机理,并对一些重要进展进行梳理和凝练。同时,对其研究与实践的未来方向进行了展望,为学术研究和业界应用提供关于决策偏差的深入洞察,以期实现“知偏识正”。

基于改进遗传算法对LIRP问题集成优化研究

在物流系统优化中,物流节点的选址、库存控制及运输路径优化是进行物流系统规划最重要的模块,三个方面相互关联相互制约,在企业物流系统运作中缺一不可,也是当今企业降低成本提高利润的大势所趋.就选址、库存、车辆路径三个要素进行探讨,构建在需求不确定情形下的LIRP集成优化模型,解决分销中心的选址、库存、分销中心到需求门店的路径优化、需求门店的库存优化问题,充分将物流配送选址、库存控制、车辆路径三个方面进行有效集成,采用改进的遗传算法对模型的求解,并以连锁食品R公司为算例,编写程序代码,借助Matlab计算工具求解,最后将求解的结果进行优化对比分析,节约了R公司总里程3964 km,车辆减少36辆,总物流成本减少2.85万元,并验证了算法的有效性.

Downside Risk-Aversion Analysis for a Single-Stage Newsvendor Problem

We extend the classical newsvendor problem by introducing a downside risk constraint from the perspective of inventory control. At the beginning of a replenishment period the newsvendor will place an order, then he will review the inventory level at the end of the period. If the inventory level is positive then he will bear the holding cost and if the inventory level is negative then he will bear the backorder cost. The optimal order quantity has a simple form. We analyze the form of the optimal order quantity when we restrict that the probability that the cost level is larger than or equal to a fixed cost constant is less than a fixed value of probability. At last, we analyze the case that the fixed cost constant is equal to the expected cost.

周期可变下考虑多车型的库存路径优化研究

目的 研究基于供应商管理库存模式下,由一个供应商和多个零售商组成的二级供应链配送系统的库存路径优化问题,确定计划期内各配送周期的长度、数量,对供应链中库存策略与配送方案问题进行协调优化,使系统总成本最低。方法 考虑的成本包括库存持有成本、缺货成本和配送成本。为降低供应链系统的总成本,提出全新的周期可变策略。结果 采用遗传算法求解得出最佳方案。将不同策略的算例结果进行对比分析,结果表明周期可变策略与周期固定策略相比,系统总成本最低节约比例为1.7%,最高节约比例为42.3%。结论 通过对计划期内各配送周期的长度及数量进行划分调整可以有效地节约系统总成本,同时,采用多车型的配送方案明显优于采用同车型的配送方案。

应急物资储备中心选址研究

为了提高应急救援效率,保障应急物资供给及时性,通过熵权法改进的TOPSIS选出应急物资储备中心备选区域,进一步利用多面体不确定集合刻画需求和速度的不确定性,并以物资供应成本和交通运输时间为目标函数构建具有库存双容量限制和救援时效性限制的鲁棒优化选址模型,通过鲁棒优化选址确定最终选址,保证突发公共卫生事件下各需求点所需的物资都能得到满足.结果表明,鲁棒优化选址方案能够合理分配应急物资资源,物资供应平均运输时间2.06 h,需求满足率达到91.69%,且鲁棒优化模型在解决不确定性问题具有更好的表现.

生物质资源库存-路径整合优化问题研究

库存和路径是供应链中两个重要决策问题。本研究旨在整合优化生物质资源供应链中的设施库存和车辆路径,将总成本降至最低。本研究在优化供应链中车辆路径规划问题时,加入对设施库存问题的考虑,通过对两个问题的整合优化来减少牛鞭效应的影响。针对整合出的生物质资源供应链库存-路径优化问题建立混合整数规划模型。由于问题的计算复杂度较高,导致求解问题会消耗大量时间,为此开发混合启发式算法(HHS)实现高效决策。通过算例测试验证了模型及算法的可行性,计算结果可应用于实际的生物质资源供应链库存和路径。CPLEX精确解和HHS算法近似解的比较表明HHS算法可求得十分接近精确解的近似解且更加高效。

VMI模式下的库存路径问题及其优化算法综述

库存路径问题(IRP)是车辆路径问题和库存管理问题的结合,对供应商优化库存管理、车辆路线和交货计划,提供集成的物流解决方案具有重要意义。首先对VMI模式下库存路径问题的背景及分类进行综合分析,对引入该问题基础版本的精确算法及启发式算法的相关研究进行系统归纳梳理。针对基础版本外的随机库存路径问题,从有限计划范围和无限计划范围对相关算法的研究文献进行分类总结。最后结合问题发展趋势,对动态随机库存路径问题的研究成果进行归纳,指出IRP问题及算法将向着更加复杂的扩展层面发展。

随机需求下连锁零售企业的LIRP问题集成优化

在一个二级物流配送系统中,针对多个备选点、多个需求点的LIRP问题,以连锁零售企业H公司为例,考虑到门店分散和需求随机性的影响,建立随机需求下以总成本最小为目标的双层规划模型,通过上层规划(F)和下层规划(U)之间的关联和约束,将选址、库存和车辆路径三者进行了有效集成。通过MATLAB软件编程,第Ⅰ阶段运用免疫遗传算法和蚁群算法实现对双层规划模型的求解,第Ⅱ阶段对第Ⅰ阶段产生的初始解进行优化,以得出全局最优解,并对优化效果进行了分析。

新能源汽车制造业库存管理问题及对策研究

优化库存管理是新能源汽车制造业降本增效、稳健运营的重要举措。基于新能源汽车制造业库存管理的现状,选取业内标杆企业为案例对象,围绕价值链从购、产、销多个维度,系统分析库存管理问题的表现与成因,并给出相应的对策,为新能源汽车制造业改进库存管理提供有益的借鉴。

基于混合遗传算法的成品油二次配送优化

成品油公路运输多周期规划问题是成品油供应链的核心研究课题,属于多周期库存路径问题。该研究使用松弛下届模型加快求解速度,形成合法解的集合,将数学规划模型与改进的启发式算法相结合,在集合中快速迭代,在求解配送量时使用贪心机制得到最大收益方案。最终,在多周期循环配送算例集上测试,结果表明,可以在多数小、中规模算例中获得理论最优解,在大规模算例中平均运输成本降低12.3%。

报童问题的扩展模型

经典报童问题即单周期库存问题,研究的是面对随机需求量,零售商应该订购多少产品以获得最大的利润.报童问题是一个十分具有活力的研究问题,本文综述了报童问题近十年来的研究成果,对其扩展模型作了新的分类:决策目标的扩展模型、零售商的扩展模型、市场格局的扩展模型、供应商的扩展模型以及其他扩展模型等.

预测精度随时间变化的报童问题模型分析

在实际工作中,零售商对市场的预测一般是随时间而变化的,那么订货时间也将是库存问题的决策变量,在这种情况下,本文提出了一个推广报童问题模型,在此基础上,分析了零售商期望利润函数的性质,并且与经典报童问题模型相比较。最后用几个简单的算例说明了模型及求解方法。