Optimal inventory control of empty containers in inland transportation system

In this paper, we deal with an inventory control problem of empty containers in an inland transportation system. In inland container transportation, freights (containers) are transported between terminal and the customer’s location by trucks, trains and barges. Empty containers are an important logistic resource and shipping companies try to operate and manage empty containers efficiently. Because of the trade imbalance between hub ports, empty containers should be periodically repositioned from surplus areas to shortage areas. However, it is not easy to exactly forecast the demand of empty containers, and we therefore need to build an efficient way to reposition the empty containers. In this paper, we consider a shortage area and propose an efficient inventory policy to control empty containers. We assume that demands per unit time are independent and identically distributed random variables. To satisfy the demand of empty containers, we reposition empty containers from other hubs based on the (s, S) inventory policy, and also consider the lease of empty containers with zero lead time. For the leased containers, we should return the number of empty containers leased to the leaser after the specified period. For a given policy, simulation is used to estimate the expected cost rate and we use the optimization tool, OptQuest^® in Arena to obtain the near optimal (s, S) policy in numerical examples.     

A multi-item supply chain with credit periods and weight freight cost discounts

It is possible to realize considerable savings by aggregating the replenishment of a variety of items in a multi-item supply chain. This joint multi-item replenishment policy has already been widely applied in a variety of industries. This type of policy may make it possible for the retailer to take advantage of transport economies of scale by the utilization of freight discounts for greater weight. In addition, a supplier will often extend forward financing to a retailer. In this paper, a multi-item supply chain with a credit period and weight freight cost discounts is considered. The retailer bears the freight costs, but the freight carrier provides freight-transport discounts that are positively related to the weight of the cargo transported. From both the individual and the channel perspectives, we deal with the dual problems of determining the ideal supplier credit period, and of the best way for the retailer to make multi-item replenishment and pricing decisions, while still maximizing profits. We outline the optimal properties and develop algorithms for solving the problems described, as well as discuss the impact of the freight cost discounts, the inventory holding cost, and the interest rate on the behavior of both parties.     

Integrating noncyclical preventive maintenance scheduling and production planning for a single machine

This paper deals with the problem of integrating noncyclical preventive maintenance and tactical production planning for a single machine. We are given a set of products that must be produced in lots during a specified finite planning horizon. The maintenance policy suggests possible preventive replacements at the beginning of each production planning period, and minimal repair at machine failure. The proposed model determines simultaneously the optimal production plan and the instants of preventive maintenance actions. The objective is to minimize the sum of preventive and corrective maintenance costs, setup costs, holding costs, backorder costs and production costs, while satisfying the demand for all products over the entire horizon. The problem is solved by comparing the results of several multi-product capacitated lot-sizing problems. The value of the integration and that of using noncyclical preventive maintenance when the demand varies from one period to another are illustrated through a numerical example and validated by a design of experiment. The later has shown that the integration of maintenance and production planning can reduce the total maintenance and production cost and the removal of periodicity constraint is directly affected by the demand fluctuation and can also reduce the total maintenance and production cost.     

An examination of the economic efficiency of class I railroads: A profit function analysis

This paper uses a system of translog profit and input demand equations to analyze price and technical efficiency in Class I railroads for the period 1978–1983. The results indicate that railroads are neither profit maximizers nor cost minimizers, that capital expenditures increase technical efficiency, and that deregulation led to greater economic efficiency. The average length of haul is negatively related to economic efficiency; track miles are negatively related to economic efficiency, market share positively affects economic efficiency; and, the ratio of freight to total revenue positively affects economic efficiency.     

Ocean Carriers’ Collusion Under Antitrust Immunity: Evidence of Asymmetric Pass-Through

As fuel costs are the largest component of the shipping industry’s operating costs, this study examines whether ocean carriers pass fuel cost increases through to freight rates more quickly than they pass through fuel cost decreases. The focal price collusion theory suggests that such asymmetric pass-through could be a result of collusive behavior because collusion is easier to sustain when costs are falling than when costs are rising. Using a lag-adjustment model as the econometric framework, findings from this study show strong evidence for asymmetric adjustments of the US inbound freight rates in response to fuel cost changes. Such asymmetry persisted after the passage of the Ocean Shipping Reform Act of 1998. Moreover, the findings do not support the consumer search theory as an alternative explanation for the freight rate asymmetry.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

Modeling and optimization of a container drayage problem with resource constraints

This paper investigates the problem faced by firms that transport containers by truck in an environment with resource constraints. The considered area is export-dominant. As a result, there are three types of container movements as inbound full, outbound full, and inbound empty movements. Both the time windows at the terminal and at the customers’ places and the operation times are considered. Empty containers are also regarded as separate transportation resources besides trucks. The total operating time including waiting time of all the trucks in operation is minimized. The problem is first formulated as a directed graph and then mathematically modeled based on the graph. It falls into a multiple traveling salesman problem with time windows (m-TSPTW) with resource constraints. An algorithm based on reactive tabu search (RTS) is developed to solve the problem. A number of randomly generated examples indicate that the algorithm can be applied to the real world.     

The storage location assignment problem for outbound containers in a maritime terminal

This paper addresses the storage location assignment problem for outbound containers. The problem is decomposed into two stages. The yard bays and the amount of locations in each yard bay, which will be assigned to the containers bounded for different ships, are determined in the first stage. The exact storage location for each container is determined in the second stage. The problem in the first stage is solved by a mixed integer programming model, while a hybrid sequence stacking algorithm is applied to solve the problem in the second stage. Experimental results show that the proposed approach is effective and efficient in solving the storage location assignment problem for outbound containers.     

关于疫情影响下赶工费用的计算思路探讨

在建设项目实施过程中,经常遇到工期延误的情况.在非承包人原因(如不可抗力等)导致工期延误的情况下,为保证工期,发包人常要求承包人赶工,由此往往出现赶工费用计算的问题.以2020年新型冠状病毒肺炎疫情为例,由于受到疫情影响,大量建设项目进度滞后.随着近期国内疫情渐渐好转、各地的建设项目纷纷复工并全面展开,为避免因建设项目...     

Dynamic adjustment of container stacking policy in an automated container terminal

The decision for good stacking positions for incoming containers in an automated container terminal is an important operational problem because it affects the productivity not only for stacking but also for later retrieval. This paper proposes an online search algorithm which dynamically adjusts and optimizes a stacking policy by continuously generating variants of stacking policies and evaluating them while they are actually being applied for determining the stacking positions. Simulation experiments show that the proposed algorithm is effective in enhancing the operational productivity, while other offline optimization methods are computationally infeasible to be applied to this problem.     

A multiple ant colony optimization algorithm for the capacitated location routing problem

The success of a logistics system may depend on the decisions of the depot locations and vehicle routings. The location routing problem (LRP) simultaneously tackles both location and routing decisions to minimize the total system cost. In this paper a multiple ant colony optimization algorithm (MACO) is developed to solve the LRP with capacity constraints (CLRP) on depots and routes. We decompose the CLRP into facility location problem (FLP) and multiple depot vehicle routing problem (MDVRP), where the latter one is treated as a sub problem within the first problem. The MACO algorithm applies a hierarchical ant colony structure that is designed to optimize different subproblems: location selection, customer assignment, and vehicle routing problem, in which the last two are the decisions for the MDVRP. Cooperation between colonies is performed by exchanging information through pheromone updating between the location selection and customer assignment. The proposed algorithm is evaluated on four different sets of benchmark instances and compared with other algorithms from the literature. The computational results indicate that MACO is competitive with other well-known algorithms, being able to obtain numerous new best solutions.     

后疫情时代下新冠肺炎疫情对中国服务经济影响 ——基于多期双重差分模型的研究

本文使用中国31个省、直辖市和自治区2019年6月~2020年9月共16个月的月度面板数据,采用多期双重差分(DID)方法,分别就新冠肺炎疫情对服务业中的快递行业、金融行业、公路货运行业和进出口行业的影响展开分析,研究结果表明:疫情对快递行业和金融行业的影响有显著正向影响,对进出口企业和公路货运行业有显著负向影响。进一步,采用三重差分模型进行地区异质性与禀赋异质性检验后发现,疫情对东部地区的快递业影响不显著,对中西部地区的快递行业收入有显著正向影响;疫情对东部沿海地区的进出口总额有显著负向影响,对中西部进出口总额影响不显著;疫情对东部、中西部金融存贷款的影响均显著为正;疫情对东部地区公路货运量的影响显著为负,对中西部的影响显著为正。疫情与2019年卫生人员三重差分模型显示,对快递行业收入的影响显著为负;对公路货运量和进出口影响不显著;对金融存贷款影响显著为正。疫情与2019年人口资源禀赋三重差分模型显示,对快递行业收入、进出口总额和金融存贷款影响显著为正;对公路货运量影响不显著。     

An analysis of the end-of-aisle order picking system: Multi-aisle served by a single order picker

This study deals with an end-of-aisle order picking system in a miniload automated storage/retrieval system (AS/RS). The system has a horse-shoe style buffer at the front end of each aisle. A conveyor system delivers the containers through the buffer positions. Earlier studies for the system assumed that an order picker serves only a single aisle. In general, however, an order picker can server two or more aisles for labor cost saving, and so this paper assume that an order picker serves a number of aisles in a predetermined order. The system can be modeled as a queueing system with a limited queue length and this paper analyzes the queueing model with supplementary variable technique to find the system's long-run behavior. Then, it proposes a simple optimization model to find an optimal buffer size. To illustrate the results, some examples are included into each chapter.     

A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times,sequence-dependent setup times and learning effect

This paper addresses multi-objective (MO) optimization of a single-model assembly line balancing problem (ALBP) where the operation times of tasks are unknown variables and the only known information is the lower and upper bounds for operation time of each task. Three objectives are simultaneously considered as follows: (1) minimizing the cycle time, (2) minimizing the total equipment cost, and (3) minimizing the smoothness index. In order to reflect the real industrial settings adequately, it is assumed that the task time is dependent on worker(s) (or machine(s)) learning for the same or similar activity and sequence-dependent setup time exists between tasks. Finding an optimal solution for this complicated problem especially for large-sized problems in reasonable computational time is cumbersome. Therefore, we propose a new solution method based on the combination of particle swarm optimization (PSO) algorithm with variable neighborhood search (VNS) to solve the problem. The performance of the proposed hybrid algorithm is examined over several test problems in terms of solution quality and running time. Comparison with an existing multi-objective evolutionary computation method in the literature shows the superior efficiency of our proposed PSO/VNS algorithm.     

Optimal pricing and order quantity for the newsvendor problem with free shipping

To attract and keep customers, companies, especially those in e-business, are increasingly offering free shipping to buyers whose order sizes exceed the free shipping quantity. In this paper, given the supplier offers free shipping and the retailer faces stochastic demand, we determine the retailer's (i.e., the newsvendor's) optimal order quantity and the optimal selling price simultaneously. We consider two different ways in which price affects the demand distribution, namely price only affects the location or scale of the demand distribution. We explicitly incorporate the supplier's quantity discount and transportation cost into the models. The transportation cost function is very general, which includes those most commonly used in the literature. We numerically examine the impacts of free shipping, quantity discount, transportation cost, and demand variance on the retailer's optimal order quantity and pricing decisions. We find that even though the retailer faces uncertain demand, free shipping can effectively encourage the retailer to order more of the good and can benefit the supplier, the retailer, and the end customers. An increase in transportation cost or a decrease in purchase price will induce the retailer to order more of the good and decrease the retail price. With increasing demand variance, the retailer should order more of the good. We also find that the newsvendor can cope with demand variance by taking advantage of free shipping.     

An inventory model with deteriorating items under inflation when a delay in payment is permissible

This study develops an inventory model for initial-stock-dependent consumption rate when a delay in payment is permissible. In the inventory model, shortages are not allowed. The effect of the inflation rate, deterioration rate, initial-stock-dependent consumption rate and delay in payment are discussed. In the study, mathematical models are also derived under two different circumstances, i.e., Case I: The credit period is less than or equal to the cycle time for settling the account; and Case II: The credit period is greater than the cycle time for settling the account. Besides, expressions for an inventory system's total cost are derived for these two cases. Moreover, a computational procedure and GINO (Lasdon et al., ACM Transactions Mathematical Software 4 (1978) 34–50) are proposed to obtain the optimal order size and cycle time. The results can help managers determine the optimal total cost. Finally, a numerical example demonstrates the applicability of the proposed model.     

A decision model for adopting an extended warranty under different maintenance policies

Numerous products are sold with a warranty period and the possibility of buying an extended warranty for a given additional cost. The buyer has then to decide to take the extended warranty or not when purchasing the product. We develop in this paper a mathematical model to study the opportunity provided by the extended warranty for the buyer as well as for the manufacturer. The total average cost incurred by each side during the product’s life cycle is expressed in order to determine the maximum extra cost the consumer should pay and the minimum price at which the manufacturer should sell the extended warranty. This is done under different options in terms of maintenance strategies adopted during the product’s lifecycle.     

The selective pickup and delivery problem: Formulation and a memetic algorithm

The pickup and delivery problem addresses the real-world issues in logistic industry and establishes an important category of vehicle routing problems. The problem is to find the shortest route to collect and distribute commodities under the assumption that the total supply and the total demand are in equilibrium. This study presents a novel problem formulation, called the selective pickup and delivery problem (SPDP), by relaxing the constraint that all pickup nodes must be visited. Specifically, the SPDP aims to find the shortest route that can supply delivery nodes with required commodities from some pickup nodes. This problem can substantially reduce the transportation cost and fits real-world logistic scenarios. Furthermore, this study proves that the SPDP is NP-hard and proposes a memetic algorithm (MA) based on genetic algorithm and local search to resolve the problem. A novel representation of candidate solutions is designed for the selection of pickup nodes. The related operators are also devised for the MA; in particular, it adapts the 2-opt operator to the sub-routes of the SPDP for enhancement of visiting order. The experimental results on several SPDP instances validate that the proposed MA can significantly outperform genetic algorithm and tabu search in terms of solution quality and convergence speed. In addition, the reduced route lengths on the test instances and the real-world application to rental bikes distribution demonstrate the benefit of the SPDP in logistics.     

Optimal Size in the Waste Collection Sector

The purpose of this study is to analyze the cost structure of a sample of Italian wastecollection firms in order to assess economies of scale and density and, therefore, definethe optimal size of the firms. A total and a variable translog cost function were estimated using panel data for a sample of 30 firms operating at the provincial level over the period 1991–1995.The empirical evidence suggests that franchised monopoly, rather than side-by-sidecompetition, is the most efficient form of production organization in the waste collection industry. Further, the majority of firms are not operating at optimal scale.     

石家庄市3月份非典型大气污染过程分析

为探究空气质量变化的成因,对近5年石家庄市3月份的气象、环境监测资料进行归纳整理,并重点分析了2016年3月份石家庄市的污染状况及其影响因素。统计数据表明,下半月(非采暖期)的污染状况总体上严重于上半月(采暖期),这主要有3个方面的原因:一是用煤量虽逐渐减少,但经济活动增加导致的大气污染物排放量大幅度增加,二是汽车保有量不断增加,以及日益活跃的工业生产活动导致的重型货运车运输量增大,三是区域气象条件导致的扬尘污染。建议石家庄市3月份重点削减工业用煤和民用煤的使用量,加强面源的污染控制,并加强对大型货车及各类工地的管控。