基于收益管理的海运集装箱舱位分配与路径选择优化模型

文章应用收益管理的方法对不确定环境下海运集装箱的舱位分配问题进行了定量研究.首先针对海运收益管理的应用特征,建立了考虑空箱调运和路径选择的集装箱多航段能力分配模型,然后考虑需求的不确定性,应用稳健优化方法对此模型进行求解.最后,通过数值仿真得到了优化的舱位分配方案,比较发现稳健优化模型取得了较确定性规划模型更好的收益.显示了模型和方法对于集装箱海运企业的收益管理问题具有应用价值.     

考虑长期运力合同的班轮收益管理运输路径优化模型

基于收益管理的方法,文章对随机需求环境下班轮运力分配和路径优化问题进行了定量研究。首先针对海运收益管理的特征,建立了考虑长期运力合同、空箱调运的轮运力分配和路径选择随机规划模型,然后应用稳健优化方法对此模型进行求解。最后,通过数值仿真得到了优化的舱位分配方案,比较发现稳健优化模型取得了较确定性规划模型更好的收益,显示了模型和方法对于集装箱海运企业的收益管理问题具有应用价值。     

海运集装箱收益管理舱位动态控制策略研究

文章基于收益管理的思想对不确定环境下集装箱班轮的动态舱位分配问题进行了定量研究.考虑了班轮运输业中的团体预订行为,建立了离散时间、离散状态的随机动态规划模型,并分别对考虑团体需求和不考虑团体需求模型的性质进行了分析,提出了在不考虑团体需求情况下的阈值控制策略并指出了在考虑团体需求情况下该策略不成立的情况,最后,用数值仿真对以上性质和策略进行了验证.     

高速铁路客运专线的收益管理模型

本文在分析铁路客运收益管理的研究进展的基础上,提出了一个适合铁路客运专线的收益管理优化模型。模型以列车运营总收益最大化为目标,优化列车的席位控制和发车间隔,将席位分配与运营能力优化统一在一个模型中。利用随机生成数据进行的模型试验表明,模型可以在较短的时间内求解较大规模的收益管理优化问题。     

集装箱码头泊位计划干扰恢复多目标模型

研究集装箱码头中干扰事件发生后泊位计划的调整问题,目的是降低干扰事件对集装箱码头作业系统的干扰.基于干扰管理方法,建立泊位计划干扰恢复多目标、多阶段模型,该模型考虑码头不同客户的特点以及多方利益的平衡,从码头作业成本、船舶延误以及计划偏离度三个方面度量系统扰动.为求解模型,提出了基于字典续的求解方法,并利用算例对模型与算法的有效性进行了验证.结果表明:该模型与算法可以有效解决泊位计划调整问题,模型能够考虑各方的利益以及码头各类客户的特点,因此得到的泊位调整方案更科学,同时,模型各目标的重要顺序可根据情况进行调整,实用性与可操作性更高.     

运输网络运量分配问题的模型及算法研究

针对我国在运量分配模型及算法方面研究比较薄弱的现状,本文对此问题进行了系统深人的研究,应用运筹学、计算机科学的新的理论和方法,建立了多目标运量分配优化模型,且在模型中,将一些重要特性考虑成运输流量的函数,从而可使分配结果更符合实际情况。同时为求解该模型,本文研究设计了鲁棒性强、高效、实用的自适应搜索算法。     

带有多级制造环节的供应链能力分配方法及应用

针对生产过程具有多级制造环节的供应链能力分配问题,在考虑生产能力、市场容量、合同需求等约束的基础上,建立了混合整数非线性规划数学模型.基于约束满足技术进行问题求解,采用先确定后逆向回溯赋值的机制保证解的可行性.通过仿真实验和应用案例验证了模型与算法的可行性和有效性.     

顾客视角下的饭店收益管理

收益管理,是20世纪80年代在欧美发达国家开始应用的一种先进而成功的管理方法,而我国的研究和应用起步较晚,且大多从饭店角度出发,仅考虑如何使饭店收益最大化,没有考虑顾客的感受和长远利益。本文以顾客的视角,在阐述收益管理的概念和使用条件的基础上,论述了收益管理的系统模型和管理方法,希望通过实施收益管理,促进饭店短期与长期收益均达到最大化。     

考虑船舶速度偏差的集装箱班轮运输货运收益鲁棒优化

由于受到天气、海况及航路环境等不确定因素的影响，船舶实际航速常常与计划航速产生偏差，导致班轮运输的航次加油和货物装运策略也产生变化，进而对船舶燃油成本和运费收入产生影响。因此，考虑速度偏差的集装箱班轮运输收益优化研究具有重要的现实意义。为了保证速度偏差不确定性下的各航段船舶航行用油安全，以船舶到达下一挂靠港的船期时间窗为约束，推导得出速度偏差最大情况下的船舶航段最大燃油消耗量显性函数，结合各加油港燃油价格及折扣差异，以及集装箱货物各O-D流量及运费率差异，以班轮运输航次收益鲁棒优化为目标，构建了速度偏差下的集装箱班轮运输收益混合整数非线性规划模型，设计分段线性割线逼近算法进行模型求解。以中国远洋海运集团有限公司的MEX航线数据为实际算例进行了分析验证，结果显示：考虑速度偏差的班轮运输加油和货物装运全局鲁棒优化策略能够有效地提高班轮运输航次货运收益；随着船舶燃油消耗系数和各航段速度偏差极值的增加，班轮运输航次燃油消耗量也随之增加，而航次运费收入和货运收益都将随之减少。研究结论可为船公司制定速度偏差下的集装箱班轮运输决策提供有益的参考。     

基于免疫遗传算法和列生成的多项目人力资源调度研究

主要研究列生成法求解带有人力资源约束的多项目多模式进度管理问题。首先根据问题建立了相应的数学模型,模型中考虑了多种约束,如项目对人员能力、水平的不同要求,目标为满足约束的条件下成本最小化,其中包含固定和可变两类成本。模型分解后,按照列生成法流程求解。由于问题的复杂性,采用启发式算法求解每个子问题:首先由基于优先原则的启发式方法给出问题的初始解,再由免疫遗传算法寻优。通过数值实验分析了算法性能、模型改进情况,不同优先原则组合对目标成本和各项目间时间分配的影响。     

Tighter MIP models for Barge Container Ship Routing

This paper addresses the problem of optimal planning of a liner service for a barge container shipping company. Given estimated weekly demands between pairs of ports, our goal is to determine the subset of ports to be called and the amount of containers to be shipped between each pair of ports, so as to maximize the profit of the shipping company. In order to save possible leasing or storage costs of empty containers at the respective ports, our approach takes into account the repositioning of empty containers. The line has to follow the outbound–inbound principle, starting from the port at the river mouth. We propose a novel integrated approach in which the shipping company can simultaneously optimize the route (along with repositioning of empty containers), the choice of the final port, length of the turnaround time and the size of its fleet. To solve this problem, a new mixed integer programming model is proposed. On the publicly available set of benchmark instances for barge container routing, we demonstrate that this model provides very tight dual bounds and significantly outperforms the existing approaches from the literature for splittable demands.We also show how to further improve this model by projecting out arc variables for modeling the shipping of empty containers. Our numerical study indicates that the latter model improves the computing times for the challenging case of unsplittable demands. We also study the impact of the turnaround time optimization on the total profit of the company.     

The Critical Role of Ocean Container Transport in Global Supply Chain Performance

With supply chains distributed across global markets, ocean container transport now is a critical element of any such supply chain. We identify key characteristics of ocean container transport from a supply chain perspective. We find that unlike continental (road) transport, service offerings tend to be consolidated in few service providers, and a strong focus exists on maximization of capital intensive resources. Based on the characteristics of ocean container transport as part of global supply chains, we list a number of relevant and challenging research areas and associated questions.     

Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters

We consider assortment optimization problems under the multinomial logit model, where the parameters of the choice model are random. The randomness in the choice model parameters is motivated by the fact that there are multiple customer segments, each with different preferences for the products, and the segment of each customer is unknown to the firm when the customer makes a purchase. This choice model is also called the mixture‐of‐logits model. The goal of the firm is to choose an assortment of products to offer that maximizes the expected revenue per customer, across all customer segments. We establish that the problem is NP complete even when there are just two customer segments. Motivated by this complexity result, we focus on assortments consisting of products with the highest revenues, which we refer to as revenue‐ordered assortments. We identify specially structured cases of the problem where revenue‐ordered assortments are optimal. When the randomness in the choice model parameters does not follow a special structure, we derive tight approximation guarantees for revenue‐ordered assortments. We extend our model to the multi‐period capacity allocation problem, and prove that, when restricted to the revenue‐ordered assortments, the mixture‐of‐logits model possesses the nesting‐by‐fare‐order property. This result implies that revenue‐ordered assortments can be incorporated into existing revenue management systems through nested protection levels. Numerical experiments show that revenue‐ordered assortments perform remarkably well, generally yielding profits that are within a fraction of a percent of the optimal.     

Dynamic pricing and revenue management process in Internet retailing under uncertainty: An integrated real options approach

Competition and demand volatility often cause modern enterprises to be confronted by uncertain environments. When a firm manages revenue in such competitive and risky environments, the optimization of pricing and capacity allocation, subject to a fixed time and capacity, becomes a complicated problem. Many previous papers concerning revenue management (RM) and pricing require that the firm possesses the ability to know the demand curve (or demand distribution) and set prices on it to maximize profits. However, this assumption may not be the case in some industries. Therefore, this paper focuses on the dynamic lead indicators rather than assumptive lag indicators to establish a concise and flexible decision model for practical use. This paper provides an integrated real options (IRO) approach with analytic hierarchy process (AHP) for the auction RM problem under competitive/dynamic pricing and revenue uncertainty in Internet retailing. A numerical example is also presented to illustrate that the IRO approach can generate better decisions than the naı¨ve (or risk unawareness) approach in revenue quality of safety and profitability. The new perspective and approach proposed by this paper can be extended to other RM fields whenever both profitability and risk are critical to decision making.     

Multi-item single-source ordering with detailed consideration of transportation capacities

We consider multi-item single-source ordering with detailed consideration of transportation capacities. Such problems are characteristic for companies which operate direct links as part of their supply chain to transport loads with heterogeneous physical dimensions and fluctuating demands. Given knowledge on transportation demands, companies can eliminate future transports by shifting the load to fill the inflexible capacity of prior transports. While reducing transportation costs, doing so will ceteris paribus imply inventory. The problem is to coordinate orders across multiple items such that transport costs are minimized at minimal increase in inventory. The approach is distinct from prior works in that it considers detailed loading restrictions. We therefore interpret the problem as a multi-period version of the container loading problem. A wall building approach is used and incorporated into a heuristic rolling horizon procedure. We test the proposed procedure on some random problems which resemble a real inbound case from the automotive industry. As compared to period-by-period planning and two benchmarks with aggregated capacity models from the literature and practice, cost savings are possible under a wide range of operating conditions and mostly independent of the shipping volume. The largest potential exists for mid- to long-distance transports. There is a relevant potential to improve short-distance transports as well, however, only if inventory cost rates are moderate.     

集装箱班轮二维收益管理在线动态定价策略

为了在现实约束条件下最大化班轮公司收益,研究了集装箱海运二维收益管理多航段多箱型在线动态定价模型,提出了其最优在线动态定价策略,并且证明了模型价值函数的单调性及其上界.基于降维的思想提出了更为实际的启发式算法.在算例中分析了单航段单箱型、单航段多箱型和多航段多箱型3种情况下的最优动态定价策略,分析结果表明:在单航段单箱型的情况下,最优价格具有单调性;在单航段多箱型和多航段多箱型的情况下,最优价格不一定具有单调性.     

Container Scheduling: Complexity and Algorithms

We consider the transport of containers through a fleet of ships. Each ship has a capacity constraint limiting the total number of containers it can carry and each ship visits a given set of ports following a predetermined route. Each container has a release date at its origination port, and a due date at its destination port. A container has a size 1 or size 2; size 1 represents a 1 TEU (20‐foot equivalent unit) and size 2 represents 2 TEUs. The delivery time of a container is defined as the time when the ship that carries the container arrives at its destination port. We consider the problem of minimizing the maximum tardiness over all containers. We consider three scenarios with regard to the routes of the ships, namely, the ships having (i) identical, (ii) nested, and (iii) arbitrary routes. For each scenario, we consider different settings for origination ports, release dates, sizes of containers, and number of ports; we determine the computational complexity of various cases. We also provide a simple heuristic for some cases, with its worst case analysis. Finally, we discuss the relationship of our problems with other scheduling problems that are known to be open.     

Randomization Approaches for Network Revenue Management with Customer Choice Behavior

In this study, we present new approximation methods for the network revenue management problem with customer choice behavior. Our methods are sampling‐based and so can handle fairly general customer choice models. The starting point for our methods is a dynamic program that allows randomization. An attractive feature of this dynamic program is that the size of its action space is linear in the number of itineraries, as opposed to exponential. It turns out that this dynamic program has a structure that is similar to the dynamic program for the network revenue management problem under the so called independent demand setting. Our approximation methods exploit this similarity and build on ideas developed for the independent demand setting. We present two approximation methods. The first one is based on relaxing the flight leg capacity constraints using Lagrange multipliers, whereas the second method involves solving a perfect hindsight relaxation problem. We show that both methods yield upper bounds on the optimal expected total revenue. Computational experiments demonstrate the tractability of our methods and indicate that they can generate tighter upper bounds and higher expected revenues when compared with the standard deterministic linear program that appears in the literature.