Reheat furnace scheduling with energy consideration

This paper focuses on the reheat furnace scheduling problem (RFSP) which is to assign the slabs to the reheat furnace, make the slab sequence for each furnace and determine the feed-in time and the residence time for each slab in order to reduce the unnecessary energy consumption reflected by minimising the objective under consideration. Differing from the traditional scheduling problem, the actual residence time of each slab in RFSP needs to be decided and it is correlated with its neighbour slabs in the reheating sequence of the same furnace. Firstly, the RFSP is formulated as a mixed integer programming model with consideration of the practical production requirements. The strong NP-hardness of the problem motivates us to develop a scatter search (SS) algorithm to solve the problem approximately. The SS algorithm is improved by constraint propagation (CP) for filtering the infeasible solutions in both the generation of the initial solutions and the improvement procedure. To verify the algorithm performance, the proposed algorithm is compared with ILOG CP Optimiser for small-scaled problems and the standard SS, genetic algorithm (GA) for large-scaled practical problems, respectively. The computational results illustrate that the proposed algorithm is relatively effective and efficient.     

集装箱码头岸吊作业调度建模及调度策略研究

岸吊作业调度对集装箱码头整体运营效率具有重要影响.综合考虑岸吊实际作业中的特有约束,包括预定义顺序约束、依赖于作业次序的设备调整时间、岸吊干涉约束,建立岸吊作业调度问题的混合整数规划模型.针对混合装卸模式,使用启发式算法生成预定义作业顺序,在此基础上采用基于连续贝作业策略的启发式算法对问题进行求解.数据实验结果显示基于SPT规则和连续贝作业的启发式算法能有效利用混合装卸带来的时间节省,减少设备调整时间,对实际岸吊作业调度具有指导意义.     

A nested column generation algorithm to the meta slab allocation problem in the steel making industry

This paper addresses one of the key operational decision problems in the steel industry which is related to the allocation of orders to stock materials in the surplus inventory. The meta slab allocation problem can be stated as the ‘multi-stage multiple knapsack problem’ where the problem is to design slabs using orders with similar properties (the first stage) and allocating these designed slabs into the existing meta slabs in the inventory yard (the second stage). The objective of the problem is to maximise the allocated order weights in slabs and meta slabs. For the given problem, we propose a column generation algorithm, where a column in the master problem represents meta slabs and the sub problem is to design ‘bins’, here slabs with the given orders. The sub problem itself also becomes a multiple knapsack problem and we proposed a practical set-partitioning heuristic. The proposed algorithm was tested with daily operation data given from an integrated steel company in the Asia Pacific. The computational results showed that the proposed heuristic solved the real instances pretty well. The proposed algorithm was successfully deployed to the integrated steel mill.     

Modelling and a genetic algorithm solution for the slab stack shuffling problem when implementing steel rolling schedules

Iron and steel production is a multistage process. A slab yard serves as a storage buffer between the continuous casting stage and the steel rolling mill. Slabs from continuous casting are stacked in the yard to await rolling. When implementing the rolling production schedule, slabs need to be picked up from the slab yard one by one according to the scheduled rolling sequence, heated in the heating furnace and then rolled. There are usually a number of suitable candidate slabs in the yard satisfying the requirement for each rolling item. In general, these candidate slabs are not at the most convenient positions in the stacks. To pick up a required slab, the slabs above it need to be shuffled. To save slab-handling cost and prevent the handling cranes from becoming a bottleneck, slabs for a rolling schedule must be selected from among the candidate slabs so that the total number of slabs shuffled is minimized. The paper studies the slab stack-shuffling problem using the hot strip rolling mill in Shanghai Baoshan Iron and Steel Complex as an application background. We first formulate the problem using an integer-programming model and then develop a modified genetic algorithm to solve it. Genetic codes and genetic operators are specially designed to ensure the feasibility of solutions and to speed up the solution process. The algorithm is implemented and compared with the existing algorithm that the mill has been using. Experiments on randomly generated problems show that the proposed new method reduces the number of slab shuffles by 11.19% on average.     

An effective heuristic for scheduling a yard crane to handle jobs with different ready times

In land-constrained port container terminals, yard cranes are commonly used for handling containers in a container yard to load containers onto or unload containers from trucks. However, yard cranes are bulky, slow and need to move frequently between their work locations. As it is common that the container flow in a terminal is bottlenecked by yard crane operations, effective work schedules of yard cranes are needed to increase the terminal’s throughput. This article studies the problem of scheduling a yard crane to perform a given set of container handling jobs with different ready times. The objective is to minimize the sum of job waiting times. It is noted that the scheduling problem is NP-complete. This research develops a heuristic to solve the scheduling problem and an algorithm to find lower bounds for benchmarking the schedules found by the heuristic. The performance of the heuristic is evaluated by a set of test problems generated on the basis of real-life terminal operations data. Indeed, the computational results show that the proposed heuristic can find effective solutions for the scheduling problem.     

Quay crane scheduling for an indented berth

This article explores the quay crane scheduling problem at an indented berth. The indented berth is known as an innovative implementation in the container terminals to tackle the challenge from the emergence of more and more mega-containerships. A mixed integer programming model by considering the non-crossing and safety distance constraints is formulated. A Tabu search heuristic is developed to solve the proposed problem. The computational results from this research indicate that the designed Tabu search is an effective method to handle the quay crane scheduling problem at an indented berth.     

Quay crane scheduling in container terminals

The problem of scheduling identical quay cranes moving along a common linear rail to handle containers for a ship is studied. The ship has a number of container-stacking compartments called bays, and only one quay crane can work on a bay at the same time. The objective of the scheduling problem is to find the work schedule for each quay crane which minimizes the ship’s stay time in port. Finding the optimal solution of the scheduling problem is computationally intractable and a heuristic is proposed to solve it. The heuristic first decomposes the difficult multi-crane scheduling problem into easier subproblems by partitioning the ship into a set of non-overlapping zones. The resulting subproblems for each possible partition are solved optimally by a simple rule. An effective algorithm for finding tight lower bounds is developed by modifying and enhancing an effective lower-bounding procedure proposed in the literature. Computational experiments were carried out to evaluate the performance of the heuristic on a set of test problems randomly generated based on typical terminal operations data. The computational results show that the heuristic can indeed find effective solutions for the scheduling problem, with the heuristic solutions on average 4.8% above their lower bounds.     

Modelling and a tabu search solution for the slab reallocation problem in the steel industry

This paper considers a slab reallocation problem arising from operations planning in the steel industry. The problem involves reallocating steel slabs to customer orders to improve the utilisation of slabs and the level of customer satisfaction. It can be viewed as an extension of a multiple knapsack problem. We firstly formulate the problem as an integer nonlinear programming (INLP) model. With variable replacement, the INLP model is then transformed into a mixed integer linear programming (MILP) model, which can be solved to optimality by MILP optimisers for very small instances. To obtain satisfactory solutions efficiently for practical-sized instances, a heuristic algorithm based on tabu search (TS) is proposed. The algorithm employs multiple neighbourhoods including swap, insertion and ejection chain in local search, and adopts solution space decomposition to speed up computation. In the ejection chain neighbourhood, a new and more effective search method is also proposed to take advantage of the structural properties of the problem. Computational experiments on real data from an advanced iron and steel company in China show that the algorithm generates very good results within a short time. Based on the model and solution approach, a decision support system has been developed and implemented in the company.     

Quay crane scheduling with dual cycling

In this article, the dual cycling quay crane scheduling problem (D-QCSP) with hatches is addressed to minimize the operation cycles of quay cranes. The problem is decomposed into two sub-problems: the intra-group stage (sequencing stacks within each hatch) and the inter-group stage (scheduling all hatches). A new stack sequencing method is constructed for stacks of each hatch, which is modelled as a two-machine non-permutation flow shop scheduling problem. By removing inner gaps using left-shifting, the adapted hatch scheduling sub-problem is modelled as a two-machine grouped flow shop scheduling problem, which contains more precise processing times. A composite heuristic is proposed for the D-QCSP. Based on the derived lower bound, the heuristic is compared with the best existing heuristics on a large number of instances. Experimental results illustrate that the proposal outperforms the existing methods on all instances and dual cycling needs many fewer quay crane operating cycles than single cycling.     

A 0-1 integer programming model and solving strategies for the slab storage problem

We consider the slab storage problem (SSP) in slab yard operations. A set of slabs enter a slab yard in a specific order. A proper stack needs to be selected for each inbound slab, so that the number of relocations in the subsequent retrieval stage is minimised. We present a 0-1 integer programming model of the SSP that minimises the lower bound of the number of relocations. Four solving strategies are derived from several interesting properties of the mathematical model to speed up the solving process of the model. Making use of randomly generated instances and practical instances, we testify the effectiveness of the solving strategies and study the influence of problem parameters on the computational time of the model. Computational results show that the solving strategies can effectively reduce the computational time of the model and is applicable in medium-sized practical instances.     

考虑作业效率差异的同类岸桥作业调度优化

针对集装箱港口岸桥调度过程中,岸桥具有作业效率差异的特点,将其视为同类平行机调度问题,同时结合岸桥作业不可相互穿越与安全距离等特有约束,建立了更加符合实际的岸桥作业调度混合整数规划模型,其优化目标是最小化装卸作业的最大完工时间。针对问题的NP-hard特性,设计了求解模型的遗传算法,对算法搜索空间进行了讨论,并推导了问题的下界。最后,通过实验算例验证了模型与算法的有效性。     

Logistics optimisation of slab pre-marshalling problem in steel industry

We study the slab pre-marshalling problem to re-position slabs in a way that the slabs are stored in the least number of stacks and each stack contains only the slabs of the same group, which can be utilised interchangeably. In this way, when a slab of any group is required, the topmost slab can always be picked up without shuffling. During pre-marshalling, however, at most two slabs can be moved by one operation. In this paper, we present a network model with three valid inequalities to solve this problem. With a small amount of labelled data from the model approach, a self-training technique is applied to train a function for predicting the best next move. Then, a new hybrid algorithm is developed to solve the practical problems by combining the self-training technique, heuristics, and the branch-and-bound algorithm with five dominance rules. The experimental results demonstrate the effectiveness of this network model and valid inequalities, and the performances of different components of this algorithm. The new algorithm produces high-quality solutions within seconds.     

A design model for punching shear of FRP-reinforced slab-column connections

The overall aim of this paper is to develop a unified design method for the punching shear resistance of slab-column connections irrespective of the type of internal reinforcement. In the first part of the paper a design model for the punching shear resistance of concrete slab-column connections reinforced with fibre-reinforced polymers (FRP) is proposed. This design model is based on the authors’ theoretical analysis for such slabs, which considers the physical behavior of the connections under load. The effects of the inherent linear brittle response, the lower elastic modulus and the different bond features, as compared to steel, of the FRP reinforcement are all accounted for in the present study. The proposed model does not incorporate any fitting factors to match the theory to the trend of the available FRP slab test results. The excellent agreement between the predicted and published test results should give confidence to engineers and designers in using FRP as a sound structural reinforcement for slab-column connections.

It is then shown that the proposed design model for FRP slabs and the previous model of the authors for steel reinforced slabs are both identical in nature and structure, thus constituting a unified approach to design for punching shear in slabs. On the basis of the unified model comparison and correlation between an FRP slab and a reference steel reinforced slab, confirmed by the available test results, are presented. The unified model also enables the development of a more rational and reliable equivalent steel reinforcement ratio which can be applied to existing code equations for steel reinforced slabs to estimate the punching resistance of FRP-reinforced slabs.     

混合结构房屋现浇楼板裂缝的有限元数值分析

现浇钢筋混凝土楼板开裂是混合结构房屋常遇到的问题之一。在对若干实际工程调查和模型试验的基础上,用有限元程序建立了两种结构形式的有限元模型,进行了非线性有限元分析。有限元分析结果包括混凝土主拉应力及应变、楼板裂缝和钢筋应力的分布和发展,其与试验结果符合程度较好。研究结论给出了楼板开裂的主要原因和影响因素、裂缝形态及范围、控制裂缝的关键措施和楼板钢筋合理的布置方式。     

钢纤维混凝土方形板的冲切强度统一解

该文基于统一强度理论对钢纤维混凝土方形板的冲切承载力进行了理论分析,推导了冲切破坏强度的计算公式。所得的解考虑了板的抗弯能力、纵向钢筋以及材料的中间主应力效应对冲切破坏强度的影响,可以灵活地应用于各种不同材料。将该文的理论计算值与试验值进行了比较,二者吻合较好。     

A two-stage stochastic programming for single yard crane scheduling with uncertain release times of retrieval tasks

Nowadays maritime transportation has become the mainstream of the global logistics, and the operational efficiency of container terminals plays a critical role in maritime transportation. As one of the most important terminal operational issues, yard crane scheduling that handles both storage and retrieval tasks has caught a lot of interest. However, the uncertainty on the release times of retrieval tasks, as one common phenomenon in daily operations, has been ignored in the literature. This paper investigates single yard crane scheduling to minimise the expected total tardiness of tasks, and focus on the case with uncertain release times of retrieval tasks. A two-stage stochastic programming model is proposed, and the sample average approximation (SAA) approach is applied to solve small instances of the problem. For large-scale instances, a genetic algorithm (GA) and a rule-based heuristic are developed. To evaluate the performances of the solution methods, numerical experiments with 300 instances are implemented. Computational results show that the rule-based heuristic outperforms both GA and SAA in terms of solution quality and running time.     

A workload balancing genetic algorithm for the quay crane scheduling problem

This paper proposes a novel genetic algorithm to deal with the quay crane scheduling problem (QCSP), which is known to be one of the most critical tasks in terminal operations because its efficiency and the quality of the schedule directly influence the productivity of the terminal. QCSP has been studied intensively in recent years. Algorithms in this field are concerned in the solution quality obtained and the required computational time. As QCSP is known to be NP-hard, heuristic approaches are widely adopted. The genetic algorithm proposed is constructed with a novel workload balancing heuristics, which is capable of considering the loading conditions of different quay cranes (QCs) during the reassignment of task-to-QC. The idea is modelled as a fuzzy logic controller to guide the mutation rate and mutation mechanism of the genetic algorithm. As a result, the proposed algorithm does not require any predefined mutation rate. Meanwhile, the genetic algorithm can more adequately reassign tasks to QCs according to the QCs’ loading condition throughout the evolution. The proposed algorithm has been tested with the well-known benchmark problem sets in this field and produces some new best solutions in a much shorter computational time.     

Multiple yard cranes scheduling for loading operations in a container terminal

The efficiency of yard crane scheduling is critical in increasing the throughput of a maritime terminal. This article studies the problem of scheduling multiple yard cranes in loading operations. The movements of yard cranes among container blocks and the sequencing of yard cranes within each block are studied at the same time. Potential interferences between yard cranes are considered. A mixed integer programming model is developed to formulate the problem. A genetic algorithm and a tabu search algorithm are proposed to obtain near-optimal solutions. Experimental tests are conducted to evaluate the performance of the two algorithms based on various data settings.     

Full-scale test of a pile supported steel fibre concrete slab

The aim of the short-term studies is to investigate the structural behaviour of pile supported slabs made of steel fibre concrete (SFC) only and combined reinforced steel fibre concrete. The studies include tests on an elevated slab where a combination of reinforcement bars and steel fibres have been used in one half of the slab and SFC only in the other half. The tests were performed on a column-supported elevated slab that simulates a half scale model of an industrial pile-supported floor slab. The short-term tests showed considerable structural and crack arresting performance that also increased with a higher dosage of fibres. A small addition of conventional reinforcement bars further increased the ultimate load capacity P _Max. P _Max was in the range of 125–298 kN for the two types of slab. The results indicate that SFC can be used with verifiable results in structural applications for elevated slabs and pile-supported floor slabs despite that the material testing from the ordered SFC showed a larger scatter in properties and that the calculated load capacities were only 40–220 kN. Main causes of deviance are arch and membrane effects.