Integrated mathematical optimisation approach for the tower crane hook routing problem to satisfy material demand requests on-site

Optimising decisions around the location and operation of tower cranes can improve the workflow in construction projects. Traditionally, the location and allocation problems involved in tower crane operations in the literature have been solved separately from the assignment of material supply points to demand points and the scheduling of the crane’s activity sequence across supply and demand points on a construction site. To address the gap, this paper proposes a binary integer programming problem, where location of the tower crane, allocation of supply points to material-demanding regions, and routing of hook of the crane based on activity sequencing of the hook across supply and material-demanding regions on site are optimised. The novelty in this work is in the way the crane’s activity scheduling is modelled via mathematical programming, based on routing the hook movement to meet material demand, through minimising tower crane operating costs. A realistic case study is solved to assess the validity of the model. The model is contrasted with results obtained from other solving algorithms commonly adopted in the literature, along with a solution proposed by an experienced practitioner. Results indicate that all instances can be solved when compared to other meta-heuristics that fail to achieve an optimum solution. Compared to the solution proposed by the practitioner, the results of the proposed model achieve a 46% improvement in objective function value. Planners should optimise decisions related to the location of the crane, the crane’s hook movement to meet service requests, and supply points’ locations and assignment to material-demanding regions simultaneously for effective crane operations.     

Parallel hyper heuristic algorithm based on reinforcement learning for the corridor allocation problem and parallel row ordering problem

Hyper heuristics is a relatively new optimisation algorithm. Numerous studies have reported that hyper heuristics are well applied in combinatorial optimisation problems. As a classic combinatorial optimisation problem, the row layout problem has not been publicly reported on applying hyper heuristics to its various sub-problems. To fill this gap, this study proposes a parallel hyper-heuristic approach based on reinforcement learning for corridor allocation problems and parallel row ordering problems. For the proposed algorithm, an outer layer parallel computing framework was constructed based on the encoding of the problem. The simulated annealing, tabu search, and variable neighbourhood algorithms were used in the algorithm as low-level heuristic operations, and Q-learning in reinforcement learning was used as a high-level strategy. A state space containing sequences and fitness values was designed. The algorithm performance was then evaluated for benchmark instances of the corridor allocation problem (37 groups) and parallel row ordering problem (80 groups). The results showed that, in most cases, the proposed algorithm provided a better solution than the best-known solutions in the literature. Finally, the meta-heuristic algorithm applied to three low-level heuristic operations is taken as three independent algorithms and compared with the proposed hyper-heuristic algorithm on four groups of parallel row ordering problem instances. The effectiveness of Q-learning in selection is illustrated by analysing the comparison results of the four algorithms and the number of calls of the three low-level heuristic operations in the proposed method.     

A modified teaching–learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling

In this paper, a modified teaching–learning-based optimisation (mTLBO) algorithm is proposed to solve the re-entrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. Based on the simple job-based representation, a novel decoding method named equivalent due date-based permutation schedule is proposed to transfer an individual to a feasible schedule. At each generation, a number of superior individuals are selected as the teachers by the Pareto-based ranking phase. To enhance the exploitation ability in the promising area, the insertion-based local search is embedded in the search framework as the training phase for the TLBO. Due to the characteristics of the permutation-based discrete optimisation, the linear order crossover operator and the swap operator are adopted to imitate the interactions among the individuals in both the teaching phase and the learning phase. To store the non-dominated solutions explored during the search process, an external archive is used and updated when necessary. The influence of the parameter setting on the mTLBO in solving the RHFSP is investigated, and numerical tests with some benchmarking instances are carried out. The comparative results show that the proposed mTLBO outperforms the existing algorithms significantly.     

Using dynamic demand information and zoning for the storage of non-uniform density stock keeping units

The warehouse order-picking operation is one of the most labour-intense activities that has an important impact on responsiveness and efficiency of the supply chain. An understanding of the impact of the simultaneous effects of customer demand patterns and order clustering, considering physical restrictions in product storage, is critical for improving operational performance. Storage restrictions may include storing non-uniform density stock keeping units (SKUs) whose dimensions and weight constrain the order-picking operation given that a priority must be followed. In this paper, a heuristic optimisation based on a quadratic integer programming is employed to generate a layout solution that considers customer demand patterns and order clustering. A simulation model is used to investigate the effects of creating and implementing these layout solutions in conjunction with density zones to account for restrictions in non-uniform density SKUs. Results from combining layout optimisation heuristics and density zoning indicate statistical significant differences between assignments that ignore the aforementioned factors and those that recognise it.     

One-side value-added service investment and pricing strategies for a two-sided platform

To widen user participation and increase profit, two-sided platforms may invest on value-added services (VASs) for users. Due to the cross-market network externality, the investment for one side would affect the utility of users on two sides, thus affect the demand and profit of the platform. In this paper, we investigate one-side VAS investment and pricing strategies for a two-sided platform. It is revealed that it is optimal to invest at the maximum level for any marginal investing cost below a certain threshold, and to decrease the investment when the marginal investing cost increases above the threshold. We find that compared with the case of no investment, the invested user side will always be priced higher, while the uninvested user side may either be priced higher or lower, depending on the relative magnitude of mutual cross-market network externalities. If both sides are priced higher after the investment, the price increment for uninvested user side could be larger than that for invested user side.     

Digital boundary tracking

In many three-dimensional imaging applications, the three-dimensional space is represented by an array of cubical volume elements (voxels) and a subset of the voxels is specified by some property. Objects in the scene are then recognised by being components of the specified set and individual boundaries are recognised as sets of voxel faces separating objects from components in the complement of the specified set. This paper deals with the problem of algorithmic tracking of such a boundary specified by one of the voxel faces lying in it. The paper is expository in that all ideas are carefully motivated and introduced. Its original contribution is the investigation of the question of whether the use of a queue (of loose ends in the tracking process which are to be picked up again to complete the tracking) is necessary for an algorithmic tracker of boundaries in three-dimensional space. Such a queue is not needed for two-dimensional boundary tracking, but published three-dimensional boundary trackers all make use of such a thing. We prove that this is not accidental: under some mild assumptions, a boundary tracker without a queue will fail its task on some three-dimensional boundaries.     

The role of topology in engineering design research

Aspects of the mathematical specialty of topology appear within several seemingly distinct areas of engineering design and engineering design theory. Indeed, the expression topology of a design is often used informally. In this article a primary intent is to demonstrate the diversity of applications of topology within engineering design. A complementary goal is to introduce the engineering design community to topology as a rich, formal, well-established mathematical discipline that may be of value for wider study. Upon reviewing some of these topological applications, it appears that topology holds promise as a basis for formalizing engineering design theory. This article considers topology as a basis for unifying design abstractions. The potential benefit may be the realization of commonalities between design aspects previously considered separately, where each now has its own attendant specialized, expensive analyses.     

基于ACO和SPN的FMS故障诊断和可用性评价方法

提出一种柔性制造系统(FMS)的故障诊断和可用性评价方法;针对传统的随机Petri网在解决FMS故障诊断上极大受限于底层马尔科夫链规模而容易产生状态爆炸的问题,首先,将蚁群优化算法(ACO)融入随机有色网(SPN)中,提出并定义了一种能对柔性制造系统的故障进行诊断的诊断器;然后,通过马尔科夫链计算制造单元的可用性,得到FMS到诊断器的映射,从而可以得到FMS中所有可能生产过程;最后,在经典FMS可用性评价方法的基础上,引入覆盖因子,提出了一种新的对FMS生产过程进行可用性评价的方法;仿真实验显示了覆盖因子对系统可用性的影响,通过与传统方法进行比较,表明覆盖因子越大,FMS的可用性越高。     

分布式结构在IP网络管理中的应用

计算机网络被日益广泛地应用,越来越深入地影响着人类的生活。随着网络规模的不断扩大,管理维护网络的任务变得越来越困难。传统的网络管理系统采用集中式结构,已经不能适应现在普遍存在的大型网络的管理需要。当前存在三种典型网络管理体系结构:集中式、分布式、分层式,通过分析比较三种结构的优缺点,可以看出分布式结构拥有最多的忧点,非常适应当前大型网络管理的需要。本文介绍了一种分布式结构的实现方式。通过选举机制,通过拓扑发现节点之间维持一种动态的主从关系,并且系统对自身节点的故障有检测手段和一定的处理措施,从而大大增强了系统的健壮性。     

IPv4&IPv6共存网络隧道发现方法研究

本文对当前IPv4&IPv6共存网络中的隧道技术进行分析,提出一套改进型的基于源路由单点探测的骨干网隧道发现方法。该方法根据路径中双栈节点间的跳数变化和PMTU变化情况发现隧道,可以发现骨干网络交叉链路中的多级隧道。这对进一步研究过渡时期的网络拓扑发现技术具有一定的参考价值。