A monolithic approach to vehicle routing and operations scheduling of a cross-dock system with multiple dock doors

Cross-docking is a logistic strategy for moving goods from suppliers to customers via a cross-dock terminal with no permanent storage. The operational planning of a cross-dock facility involves different issues such as vehicle routing, dock door assignment and truck scheduling. The vehicle routing problem seeks the optimal routes for a homogeneous fleet of vehicles that sequentially collects goods at pickup points and delivers them to their destinations. The truck scheduling problem deals with the timing of unloading and reloading operations at the cross-dock. This work introduces a mixed-integer linear programming formulation for the scheduling of single cross-dock systems that, in addition to selecting the pickup/delivery routes, simultaneously decides on the dock door assignment and the truck scheduling at the cross-dock. The proposed monolithic formulation is able to provide near-optimal solutions to medium-size problems involving up to 70 transportation orders, 16 vehicles and 7 strip/stack dock doors at acceptable CPU times.     

The multi-echelon vehicle routing problem with cross docking in supply chain management

Multi-echelon distribution networks are quite common in supply chain and logistics. Deliveries of multiple items from factories to customers are managed by routing and consolidating shipments in warehouses carrying on long-term inventories. On the other hand, cross-docking is a logistics technique that differs from warehousing because products are no longer stored at intermediate depots. Instead, cross-dock facilities consolidate incoming shipments based on customer demands and immediately deliver them to their destinations. Hybrid strategies combining direct shipping, warehousing and cross-docking are usually applied in real-world distribution systems. This work deals with the operational management of hybrid multi-echelon multi-item distribution networks. The goal of the N-echelon vehicle routing problem with cross-docking in supply chain management (the VRPCD-SCM problem) consists of satisfying customer demands at minimum total transportation cost. A monolithic optimization framework for the VRPCD-SCM based on a mixed-integer linear mathematical formulation is presented. Computational results for several problem instances are reported.     

Alternative mixed-integer linear programming models of a maritime inventory routing problem

A single product maritime inventory routing problem is addressed in this paper by exploring the use of continuous and discrete time models. We first present a continuous time model based on time slots for single docks, which is enhanced by reformulating the time assignment constraints. Next, we present a model based on event points to handle parallel docks. A discrete time is also presented based on a single commodity fixed-charge network flow problem (FCNF). All the models are solved for multiple randomly generated instances of different problems to compare their computational efficiency, and to illustrate the solutions obtained.     

A Lagrangian relaxation approach for a multi-mode inventory routing problem with transshipment in crude oil transportation

An inventory routing problem in crude oil transportation is studied, in which crude oil is transported from a supply center to multiple customer harbors to satisfy their demands over multiple periods. In the problem, a heterogeneous fleet of tankers consisting of tankers owned by a distributor and tankers rented from a third party, a pipeline, and multiple types of routes are considered; both inventory level and shortage level at each customer harbor are limited. The objective is to determine for each period over a given time horizon the number of tankers of each type to be rented/returned at the supply center, the number of tankers of each type to be dispatched on each route, and the quantity of crude oil flowing through the pipeline that minimizes the total logistics cost.After formulating the problem as a mixed integer programming problem, a Lagrangian relaxation approach is developed for finding a near optimal solution of the problem. The approach is also applied to a variant of the problem in which both fully and partially loaded tankers are allowed in the transportation of crude oil. Numerical experiments show that this approach outperforms an existing meta-heuristic algorithm, especially for the instances of large sizes.     

路径长度受限的随机需求VRP的两阶段模拟退火方法

路径长度受限的随机需求下的车辆路径问题(PSVRP)是一种普遍存在而求解困难的运筹学问题.在满足路径长度限制、只允许服务失败一次和不允许部分服务的策略下设计了一个两阶段模拟退火算法,根据模拟退火的理论容易知道算法求到的近似最优解是以概率1收敛的.对随机生成的中等规模和大规模问题做了数值试验,试验结果表明该算法有效.     

路径长度受限的随机需求VRP的节省算法及其策略分析

在保证每条路径长度限制,至多只能服务失败一次和不允许部分服务的策略下,定义了一个新的节省路径,给出了一个精确的节省算法,对中等规模和大规模问题进行了数值试验,数值试验表明算法有效。对所采用的策略进行了分析,得到了一些理论结果。     

路径长度受限的随机需求VRP的模型和算法

路径长度受限的随机需求VRP在生产、生活中有着广泛的应用。给出了路径长度受限的随机需求VRP问题的线性整数规划模型,在不允许部分服务和仅能服务失败一次的策略下设计了一个启发式算法。该算法以离散优化中广泛应用的扫描算法为基础生成服务的一个初始可行方案,然后利用模拟退火算法改进得到近似最优解。对需求为二项分布的50个结点、1个服务中心的问题进行了数值试验,数值结果表明该算法对求解路径长度受限的随机需求VRP是有效的。     

随机需求VRP的一个算法

研究了随机需求VRP问题,在服务仅能路由失败一次和不允许部分服务的情况下,给出了两阶段Clarke-Wright模拟退火算法。对需求为均匀分布的VRP问题做了数值试验,给出了具体的方案。数值结果表明这个算法比简单的两阶段模拟退火算法好,而且算法简单,容易实现。这个算法在第Ⅱ阶段模拟退火算法开始时给出了一个比较合理的初始解,较好地处理了大范围交叉的问题,从而使得模拟退火算法快速收敛到近似最优解。     

The quality‐constrained scheduling problem in plastics compounding

Interest is increasing in plastic compounding plants that offer tailor‐made resins. Such plants produce a wide range of products in small quantities and with frequent changeovers. The underlying scheduling problem has been extensively researched; however, the concept of incorporating qualities of the finished product in the problem of plastics compounding has not been considered. We express product qualities as an additional problem constraint so that the production schedule ensures product quality. The additional constraint makes this mixed integer nonlinear program (MINLP) problem more difficult to solve. Several case studies are solved to illustrate the utility of the proposed approach. Experiments demonstrated that qualities of the finished product can be ensured a priori if the appropriate relations are developed and integrated in the optimisation model. As well, this paper provides insight into the economic aspects of the scheduling problem under consideration. Experiments showed that none of the cost components (operation, raw material, inventory, penalty or utilities) can alone play the role of the optimisation criterion. © 2012 Canadian Society for Chemical Engineering     

焦化除尘灰装车扬尘的控制措施

通过平衡除尘灰仓内负压、引导旋转放灰阀空气流向、调整仓体与加湿设备连接方式等措施,除尘灰加湿装车过程下料均匀,加水顺畅,基本消除了除尘灰在装车过程中的扬尘问题,工作环境明显改善。     

综合视频监控调度系统在氯碱企业中的应用

介绍了视频监控调度系统的组成、特点及在氯碱企业中的应用情况。     

炼油企业全厂调度优化系统的设计与开发

生产调度优化对于炼油企业提高经济效益、增强市场响应速度有着重要的作用。本文设计并开发出一款图形化炼厂生产调度优化软件,采用MVC架构技术,实现了调度优化建模的图形化,可以方便组态炼油厂调度模型;将开源优化代码Coin-OR移植为调度优化软件的求解器,实现了求解器与图形化建模接口的连接;丰富的报表输出,让现场操作工可以各种形式获得调度优化结果;完善的内部模型数据管理和丰富的外部数据接口,包括原油性质指标库和原油评价数据库接口、成品油性质指标库等。仿真结果表明,该软件能够优化出符合炼厂生产实际的调度优化排产方案。     

高校课程调度系统的研究与实现

课程调度是高校教务管理的重要工作,是学校日常教学、资源合理使用的关键一环。当学校规模较小时,排课的数据量和约束条件较少,人工排课的方法尚可适用,但是随着学校规模的不断扩大,人工排课的效率和资源协调能力已经难以满足要求。文中借鉴一种需求资源矩阵的算法,对其进行了改进,并以此算法为核心,设计并实现了一个适合多校区、资源冗余较少、约束条件较多的课程调度系统,较好地解决了高校的课程调度问题。     

多效干燥过程的排产调度优化

针对干燥过程是一个高能耗的间歇单元操作,对多效干燥过程进行了排产调度研究。根据干燥速率曲线,将各效干燥过程设计为等操作时间,建立了多效干燥过程排产调度的优化模型。以效数和干燥器干燥时间为决策变量,以年费用最小为目标表达为一个混合整数非线性规划（MINLP）的数学模型,利用GAMS进行求解。以淤泥1～5效干燥为算例进行了优化调度分析,结果表明：在4效时年费用最小;与1效干燥相比,在最优条件下年生产费用可节约26%。同时获得了最优排产调度的Gantt图,从而可以得出干燥设备的最小操作周期,据此对多效干燥过程进行排产,使间歇多效干燥过程可以实现连续化生产,对多效干燥的工业化具有一定的意义。     

生产调度监控系统在化工企业中的应用

介绍了日本横河公司的工厂信息管理系统Exaquantum在化工企业中的应用。阐述了新型生产调度监控系统的系统结构、硬件配置、软件配置和系统的主要功能。     

An incremental approach using local-search heuristic for inventory routing problem in industrial gases

In this paper we solve the inventory routing problem (IRP) occurring in industrial gas distribution where liquefied industrial gases are distributed to customers that have cryogenic tanks to store the gases on-site. We consider a multi-period inventory routing problem with multiple products assuming deterministic demand rates and the proposed model is formulated as a linear mixed-integer program. We propose an incremental approach based on decomposing the set of customers in the original problem into sub-problems. The smallest sub-problem consists of the customer that needs to be delivered most urgently along with a set of its neighbors. We solve each sub-problem with the number of customers growing successively by providing the solution of the previously solved sub-problem as an input. Each sub-problem is then solved with a randomized local-search heuristic method. We also propose an objective function that drives the local-search heuristics toward a long-term optimal solution. The main purpose of this paper is to develop a solution methodology appropriate for large-scale real-life problem instances particularly in industrial gas distribution.     

Fuel production from waste vehicle tires by catalytic pyrolysis and its application in a diesel engine

An alternative fuel production was performed by pyrolysis of waste vehicle tires under nitrogen (N₂) environment and with calcium hydroxide (Ca(OH)₂) as catalyst. The sulfur content of liquids obtained were reduced by using Ca(OH)₂. The liquid fuel of waste vehicle tires(TF) was then used in a diesel engine to blend with petroleum diesel fuel by 5%(TF5), 10%(TF10), 15%(TF15), 25%(TF25), 35%(TF35), 50%(TF50), and 75%(TF75) wt. and pure (TF100). Performance characteristics such as engine power, engine torque, brake specific fuel consumption (bsfc) and exhaust temperature and emission parameters such as oxides of nitrogen (NOx), carbon monoxides (CO), total unburned hydrocarbon (HC), sulfur dioxides (SO₂) and smoke opacity of the engine operation with TF and blend fuels of TF-diesel were experimentally investigated and compared with those of petroleum diesel fuel. It was concluded that the blends of pyrolysis oil of waste tires TF5, TF10, TF25 and TF35 can efficiently be used in diesel engines without any engine modifications. However, the blends of TF50, TF75 and TF100 resulted considerably to high CO, HC, SO₂ and smoke emissions.     

遗传-分布估计算法求解化工生产中一类带多工序的异构并行机调度问题

针对化工生产中广泛存在的一类带多工序的异构并行机调度问题,即部分产品需多工序加工,同时不同产品间带序相关设置时间的异构并行机调度问题（heterogeneous parallel machine scheduling problem with multiple operations and sequence-dependent setup times, HPMSP_MOSST）,提出了一种遗传-分布估计算法（genetic algorithm-estimation of distribution algorithm, GA-EDA）,用于优化最早完工时间（makespan）。首先,提出了一种基于GA的概率模型训练机制,用来提高概率模型在算法进化初期的信息积累量,进而提高搜索的效率;其次,设计了一种有效的GA与EDA混合策略,使得算法的全局探索和局部开发能力得到合理平衡。计算机模拟验证了GA-EDA的有效性和鲁棒性。     

交通生命线系统震后应急调度模型及方法

震后交通应急调度是地震救灾工作中的一个重要环节。对震后交通生命线系统的功能进行分析,将震后道路里程、车辆速度、行程延误、交通负荷度以及路网连通可靠度等因素遴选为震后交通生命线系统的交通阻抗效用指标,提出将这些效用指标转化为一种广义交通阻抗即运输时间的理论方法,考虑到震后应急物资调度是基于时间链的动态过程,假设调度至受灾点的物资是被连续消耗的,进而建立震后多需求点多服务点应急调度的双层决策优化数学模型,给出双层规划问题的动态优化算法,得到最优的应急调度连续可行方案。通过一个仿真算例进行了验证。     

Supply chain planning and scheduling integration using Lagrangian decomposition in a knowledge management environment

The integration of planning and scheduling decisions in rigorous mathematical models usually results in large scale problems. In order to tackle the problem complexity, decomposition techniques based on duality and information flows between a master and a set of subproblems are widely applied. In this sense, ontologies improve information sharing and communication in enterprises and can even represent holistic mathematical models facilitating the use of analytic tools and providing higher flexibility for model building. In this work, we exploit this ontologies’ capability to address the optimal integration of planning and scheduling using a Lagrangian decomposition approach. Scheduling/planning sub-problems are created for each facility/supply chain entity and their dual solution information is shared by means of the ontological framework. Two case studies based on a STN representation of supply chain planning and scheduling models are presented to emphasize the advantages and limitations of the proposed approach.