Effective heuristics for the blocking flowshop scheduling problem with makespan minimization

The blocking flowshop scheduling problem with makespan criterion has important applications in a variety of industrial systems. Heuristics that explore specific characteristics of the problem are essential for many practical systems to find good solutions with limited computational effort. This paper first presents two simple constructive heuristics, namely weighted profile fitting (wPF) and PW, based on the profile fitting (PF) approach of McCormick et al. [Sequencing in an assembly line with blocking to minimize cycle time. Operations Research 1989;37:925-36] and the characteristics of the problem. Then, three improved constructive heuristics, called PF-NEH, wPF-NEH, and PW-NEH, are proposed by combining the PF, wPF, and PW with the enumeration procedure of the Nawaz-Enscore-Ham (NEH) heuristic [A heuristic algorithm for the m-machine, n-job flow shop sequencing problem. OMEGA-International Journal of Management Science 1983;11:91-5] in an effective way. Thirdly, three composite heuristics i.e., PF-NEH_LS, wPF-NEH_LS, and PW-NEH_LS, are developed by using the insertion-based local search method to improve the solutions generated by the constructive heuristics. Computational simulations and comparisons are carried out based on the well-known flowshop benchmarks of Taillard [Benchmarks for basic scheduling problems. European Journal of Operation Research 1993;64:278-85] that are considered as blocking flowshop instances. The results show that the presented constructive heuristics perform significantly better than the existing ones, and the proposed composite heuristics further improve the presented constructive heuristics by a considerable margin. In addition, 17 new best-known solutions for Taillard benchmarks with large scale are found by the presented heuristics.     

A heuristic for scheduling in a flowshop with the bicriteria of makespan and maximum tardiness minimization

This article deals with the development of a heuristic for scheduling in a flowshop with the objective of minimizing the makespan and maximum tardiness of a job. The heuristic makes use of the simulated annealing technique. The proposed heuristic is relatively evaluated against the existing heuristic for scheduling to minimize the weighted sum of the makespan and maximum tardiness of a job. The results of the computational evaluation reveal that the proposed heuristic performs better than the existing one.     

Approximation algorithms for the makespan minimization with positive tails on a single machine with a fixed non-availability interval

In this article, we consider the non-resumable case of the single machine scheduling problem with a fixed non-availability interval. We aim to minimize the makespan when every job has a positive tail. We propose a polynomial approximation algorithm with a worst-case performance ratio of 3/2 for this problem. We show that this bound is tight. We present a dynamic programming algorithm and we show that the problem has an FPTAS (Fully Polynomial Time Approximation Algorithm) by exploiting the well-known approach of Ibarra and Kim (J. ACM 22:463–468, 1975). Such an FPTAS is strongly polynomial. The obtained results outperform the previous polynomial approximation algorithms for this problem.     

A single-machine learning effect scheduling problem with release times

In this paper, we investigate a single-machine problem with the learning effect and release times where the objective is to minimize the makespan. A branch-and-bound algorithm incorporating with several dominance properties and lower bounds is developed to derive the optimal solution. A heuristic algorithm is proposed to obtain a near-optimal solution. The computational experiments show that the branch-and-bound algorithm can solve instances up to 36 jobs, and the average error percentage of the proposed heuristic is less than 0.11%.     

A note on the facility location problem with stochastic demands

In this research note that the single source capacitated facility location problem with general stochastic identically distributed demands is studied. The demands considered are independent and identically distributed random variables with arbitrary distribution. The unified a priori solution for the locations of facilities and for the allocation of customers to the operating facilities is found. This solution minimizes the objective function which is the sum of the fixed costs and the value of one of two different recourse functions. For each case the recourse function is given in closed form and a deterministic equivalent formulation of the model is presented. Some numerical examples are also given.     

A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation

The hybrid flowshop scheduling (HFS) problem with the objective of minimising the makespan has important applications in a variety of industrial systems. This paper presents an effective discrete artificial bee colony (DABC) algorithm that has a hybrid representation and a combination of forward decoding and backward decoding methods for solving the problem. Based on the dispatching rules, the well-known NEH heuristic, and the two decoding methods, we first provide a total of 24 heuristics. Next, an initial population is generated with a high level of quality and diversity based on the presented heuristics. A new control parameter is introduced to conduct the search of employed bees and onlooker bees with the intention of balancing the global exploration and local exploitation, and an enhanced strategy is proposed for the scout bee phase to prevent the algorithm from searching in poor regions of the solution space. A problem-specific local refinement procedure is developed to search for solution space that is unexplored by the honey bees. Afterward, the parameters and operators of the proposed DABC are calibrated by means of a design of experiments approach. Finally, a comparative evaluation is conducted, with the best performing algorithms presented for the HFS problem under consideration, and with adaptations of some state-of-the-art metaheuristics that were originally designed for other HFS problems. The results show that the proposed DABC performs much better than the other algorithms in solving the HFS problem with the makespan criterion.     

Minimizing the makespan on single-machine scheduling with aging effect and variable maintenance activities

This paper considers a single-machine scheduling with a position-dependent aging effect described by a power function under maintenance activities and variable maintenance duration considerations simultaneously. We examine two models of the maintenance duration in this study. The objective is to find jointly the optimal maintenance frequency, the optimal maintenance positions, and the optimal job sequences to minimize the makespan of all jobs. We provided polynomial time solution algorithms for all the studied problems.     

A note on the within-cell layout problem based on operation sequences

The existing studies in the literature usually ignore the within-cell layout problem while forming part families and manufacturing cells. A new approach is proposed to solve the part-family and machine-cell formation problem and to determine the spatial arrangement of machines in each cell simultaneously. Furthermore, a dissimilarity measure between parts based on operation sequences is presented since the operation sequences not only specify the type of machine tools needed but also impact the flow of material. As a result, we can both minimize the material handling cost and streamline the material flow in each cell.     

A note on the complexity of the problem of two-agent scheduling on a single machine

We consider a two-agent scheduling problem on a single machine, where the objective is to minimize the total completion time of the first agent with the restriction that the number of tardy jobs of the second agent cannot exceed a given number. It is reported in the literature that the complexity of this problem is still open. We show in this paper that this problem is NP-hard under high multiplicity encoding and can be solved in pseudo-polynomial time under binary encoding. When the first agent's objective is to minimize the total weighted completion time, we show that the problem is strongly NP-hard even when the number of tardy jobs of the second agent is restricted to be zero.     

A generalized procedure for minimizing makespan in a CNC environment

This paper presents the problem of scheduling N jobs, each manufactured in a number of settings, in order, on a CNC machine equipped with an automatic tool changer. A generalized procedure to minimize makespan in a CNC environment has been developed and tested on real industrial problems, considering possible constraints. It is worthy of mention that the procedure suggested finds an optimal solution of the problem discussed by Sule in a short and simplified manner. The step-by-step analysis shows the simplicity and flexibility of the proposed approach.     

A rearrangement of adjacency matrix based approach for solving the crossing minimization problem

In this paper, we first present a binary linear programming formulation for the crossing minimization problem (CMP) in bipartite graphs. Then we use the models of a modified minimum cost flow problem (MMCF) and a travelling salesman problem (TSP) to approximatively solve the CMP by rearranging the adjacency matrix of the bipartite graph. Our approaches are useful for problems defined on dense bipartite graphs. In addition, we compute the exact crossing numbers for some general dense graphs.     

领导个人学习对组织学习成效的影响：基于情境型双元平衡的视角

已有研究重点关注了领导在组织学习过程中所发挥的支持性作用,忽视了领导个人学习对组织学习成效的直接影响。为了明确领导个人学习对组织学习成效影响的内在机制,本研究提出领导可以根据组织学习情境特征,采取与之相适应的探索式学习或利用式学习,调整组织内部的纵向知识流动和横向知识流动,从而在领导个人层面实现两种学习方式的双元平衡,在组织整体层面提高组织学习成效。基于智能体的计算机仿真实验表明,当组织处于弱学习情境时,领导应采取探索式学习应对与下属之间的纵向知识流动,采取利用式学习应对与其他领导之间的横向知识流动;当组织处于强学习情境时,无论是与下属之间的纵向知识流动,还是与其他领导之间的横向知识流动,领导均应采取探索式学习,这样才有助于提高组织整体的学习成效。     

一种差异工件单机批调度问题的蚁群优化算法

由于在利用蚁群算法构建差异工件(即工件有尺寸差异)单机批调度问题的解时,批的加工时间是不确定的.从而不能类似于经典调度问题的蚁群算法把批加工时间的倒数作为蚁群算法中的启发式信息,引入批的利用率和批的负载均衡率作为蚁群算法中的启发式信息,提出了JACO(ant colony optimization based a job sequence)和BACO(ant colony optimization based a batch sequence)两种蚁群优化算法.在算法JACO中,解的编码为工件序列,它对应着用BF(best fit)分批规则生成的调度方案,信息素代表工件间的排列顺序;在算法BACO中,解的编码为批序列,信息素代表工件间的批相关性,由此信息素通过中间信息素量来构造相应的解,并引入特定的局部优化策略,提高了算法的搜索效率.实验表明,与以往文献中的SA(simula-ted annealing)、GA(genetic algorithm)算法以及FFLPT(first-fit longest processing time)、BFLPT (best-fit longest processing time)启发式规则相比,算法JACO和BACO明显优于它们,且BACO算法比JACO算法效果更好.     

A note on the deterministic EPQ with partial backordering

In a recent paper published in Omega [Pentico DW, Drake MJ, Toews C. The deterministic EPQ with partial backordering: a new approach. Omega 2009; 37(3):624–36], the authors proposed an EPQ model with partial backordering. In the EPQ model, a critical value of backordering rate was developed, below which the optimal production policy is either to lose all sales or meet all demand, above which the optimal policy is to allow stockouts with partial backordering and meet fractional demand. However, there exists a flaw in the critical value of backordering rate, which will be amended in this note.