Toward re-engineering models and algorithms of facility layout

Models and algorithms are continuously being developed for the facility layout problem in various manufacturing settings. However, there could be practices and obstacles that weaken them and adversely impact the effectiveness of the layout. Thus, they should be obliterated in order to advance the layout problem. This paper suggests a set of guidelines that are directed at the process inherent in developing layout models, algorithms, expert systems, and software applications to assist in improving them and developing better layouts. Such guidelines are lacking in the literature of facility layout. Examples on the suitability and applicability of the suggested guidelines are given.     

基于混合蚁群算法的生产系统设施规划问题研究

设施规划问题主要研究生产设备的布局规划,从而减小厂区内的物料搬运成本。一个有效的设施规划有利于生产过程中整体运作效率的提高。随着市场竞争的日趋激烈,市场环境处于不断的变化之中,制造企业需不断对设施布局进行重新规划来适应不断变化的市场环境对产品需求量的影响,并达到降低成本的目的。这一问题便需要用多阶段设施规划（MFLP）的方法来解决。本文提出了一种改进的混和蚁群算法（HACO）来解决带有财务预算约束的多阶段设施规划问题,并将此方法与其他一些典型的启发式算法进行了对比分析。结果表明,本文提出的HACO算法是求解带有财务预算约束的MFLP问题的一种有效的方法。     

Computer-aided site layout for construction projects

The paper presents two algorithms for computer aided layout of construction projects. One is a modified form of an earlier method suggested by Whitehead for a single storey building and the second uses cluster analysis. The latter results in considerable reduction of computer time. A case study is given and the results are discussed.     

Target-guided algorithms for the container pre-marshalling problem

The container pre-marshalling problem (CPMP) aims to rearrange containers in a bay with the least movement effort; thus, in the final layout, containers are piled according to a predetermined order. Previous researchers, without exception, assumed that all the stacks in a bay are functionally identical. Such a classical problem setting is reexamined in this paper. Moreover, a new problem, the CPMP with a dummy stack (CPMPDS) is proposed. At terminals with transfer lanes, a bay includes a row of ordinary stacks and a dummy stack. The dummy stack is actually the bay space that is reserved for trucks. Therefore, containers can be shipped out from the bay. During the pre-marshalling process, the dummy stack temporarily stores containers as an ordinary stack. However, the dummy stack must be emptied at the end of pre-marshalling. In this paper, target-guided algorithms are proposed to handle both the classical CPMP and new CPMPDS. All the proposed algorithms guarantee termination. Experimental results in terms of the CPMP show that the proposed algorithms surpass the state-of-the-art algorithm.     

Cellular Versus Functional Layouts Under a Variety of Shop Operating Conditions*

This paper addresses the suitability of cellular manufacturing under a variety of operating conditions. Queueing theoretic and simulation models of cellular and functional layouts are developed for various shop operating environments to investigate several factors believed to influence the benefits associated with a cellular manufacturing layout. The queueing models show how operations overlapping, which is more practical with a cellular layout, becomes more beneficial as the lot size increases. The simulation models are developed to study the performance of cellular and functional layouts in a wide variety of operating environments by varying the levels of four factors: (1) the degree to which natural part families occur, (2) the number of operations required to process the parts, (3) the processing times of the parts at each machine, and (4) the lot size. Two response variables are used to measure shop performance: the average time spent by a batch in the system, and the average work-in-process level. Statistically significant reductions in the average time in the system and average work-in-process measures were detected for the cellular layouts in all the operating environments studied.     

The dynamic plant layout problem: Incorporating rolling horizons and forecast uncertainty

To the best of our knowledge, research in the dynamic plant layout problem (DPLP) assumes that the planning horizon is fixed and that material flows are known with certainty. But in practice, many companies use rolling planning horizons. Further, they have to deal with the effect of uncertainty in material flow forecasts. This paper investigates the performance of algorithms under fixed and rolling horizons, under different shifting costs and flow variability, and under forecast uncertainty. Nearly 1800 problems were run using different algorithms. The results show that algorithms that dominated under fixed horizons may not work as well under rolling horizons. Also it is difficult to identify an algorithm that performs well under all situations. Thus the development of efficient and effective heuristics might be useful in solving the rolling horizon problem. It also appears that increasing the planning horizon under rolling plans does not offer any advantage. Further forecast uncertainty may not significantly affect the performance of algorithms and in some cases may be beneficial.     

ON PREDICTING COMPUTATIONAL TIME OF A BRANCH AND BOUND ALGORITHM FOR THE ASSIGNMENT OF FACILITIES

Experience with branch and bound algorithms indicates that computational time is a function of not only the size of the problem, but also the nature of the input data. This paper formulates statistically-based variables which describe certain characteristics of the input data and experimentally evaluates their ability to predict computational time for one branch and bound algorithm, the relative location of facilities or “plant layout” problem. Results suggest that the described experimental procedure may be useful for an a priori assessment of the computational difficulty of specific branch and bound problems.     

A simulation-based multi-objective optimization framework: A case study on inventory management

We propose a simulation-based solution framework for tackling the multi-objective inventory optimization problem. The goal is to find appropriate settings of reorder point and order quantity to minimize three objective functions simultaneously, which are the expected values of the total inventory cost, the average inventory level, and the frequency of inventory shortage. We develop new algorithms that can exploit statistically valid ranking and selection (R&S) procedures and the desirable mechanics of conventional multi-objective optimization techniques. Two simulation algorithms are proposed to be applied in different scenarios depending on the preference information that is revealed either during or after the actual optimization process. Experimental results are provided to evaluate the efficiency of the developed algorithms and other existing solution frameworks.     

An approachto the machine layout problem in a cellular manufacturing environment

The model of the machine layout problem MLP in a cellular manufacturing environment attains additional dimensions as it should satisfy the qualitative interconnections between the machines and the location restrictions of an existing factory environment. A new MLP model based on merging pre-emptive goal programming and simulated annealing has been developed for machine layout in cells. This model seeks to find feasible solutions by addressing practical issues of implementation as well as reducing the total travel distances for parts between machines. The new model can also be applied to facility layout problems FLP . The computational work is demonstrated by applying the model to problems of both quantitative and qualitative types, and has produced encouraging results. This model is particularly attractive for layout problems with realistic goals and constraints. To show the performance of the model in handling real-world problems, a practical example has been introduced and solved using the proposed model.     

Manufacturing cell formation using similarity coefficients and pair-wise interchange: formulation and comparison

Many algorithms have been proposed to form manufacturing cells from component routeings. Most of these methods require specialized algorithms for implementation. Some others use well-known procedures such as integer programming. But these may be difficult for practising managers to comprehend. In this study we propose a simple method that can be implemented using spreadsheet software and an inexpensive layout package such as CRAFT. In addition, we also compare our procedure with many existing procedures using eight well-known problems from the literature. The results show that the proposed procedure compares well with the existing procedures using three evaluation measures. Therefore, this procedure may be useful to practitioners and researchers.     

基于煤矿透水事故应急响应时效性的水泵布局鲁棒优选问题研究

为了提高煤矿透水事故中矿工获救和恢复健康的可能性，本文基于应急响应时效性研究关键资源-水泵布局问题。已有应急资源布局问题的研究多从成本、时间、资源需求满足度等方面进行，煤矿透水事故应急响应时效性是综合考虑被困矿工获救时间以及被困过程中被困位置最低氧气含量和食物缺少量三方面要素的事故应对效果。首先，建立了基于煤矿透水事故发生、发展和应急响应机理的三方面要素计算方法；然后，在供氧和供食物所需资源布局给定的前提下，设计水泵布局的目标函数和约束条件，建立水泵布局鲁棒优选模型，通过机会时间窗概念的引入和分支定界算法的思想，给出水泵布局不可行方案的判别准则，并在此基础上进行优选算法的设计；最后，在实际发生的煤矿透水事故典型案例基础上，构造算例，检验水泵布局鲁棒优选模型的有效性。     

An integrated system for capacity planning and facility layout

In order to achieve efficient facility design for service type activities, operating under dynamic conditions and a large number of constraints, the use of a traditional approach has proved to be tedious and time consuming. Development of an efficient decision support system for such a situation calls for the consideration of the complex nature of interaction between the system parameters and the relationship between the working environment and the resources within the system. Mathematical programming techniques, e.g. linear and integer programming as well as queuing models, though useful in handling combinatorial optimization problems, are incapable of dealing with stochastic utilization problems normally encountered in the design of facilities of a fast changing environment. This paper makes use of a pattern search algorithm for the optimal allocation of service facility resources. The layout of the facilities has then been optimized by the use of the CLASS algorithm. The two separate algorithms have suitably been integrated together into a single simulation-based system. The effectiveness of the proposed methodology has been demonstrated by means of a real case study pertaining to design and layout optimization of a multi-functional gasoline service station in Bangkok.     

FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms

Various methods and algorithms have been developed for multiclass classification problems in recent years. How to select an effective algorithm for a multiclass classification task is an important yet difficult issue. Since the multiclass algorithm selection normally involves more than one criterion, such as accuracy and computation time, the selection process can be modeled as a multiple criteria decision making (MCDM) problem. While the evaluations of algorithms provided by different MCDM methods are in agreement sometimes, there are situations where MCDM methods generate very different results. To resolve this disagreement and help decision makers pick the most suitable classifier(s), this paper proposes a fusion approach to produce a weighted compatible MCDM ranking of multiclass classification algorithms. Several multiclass datasets from different domains are used in the experimental study to test the proposed fusion approach. The results prove that MCDM methods are useful tools for evaluating multiclass classification algorithms and the fusion approach is capable of identifying a compromised solution when different MCDM methods generate conflicting rankings.     

Facilities design with graph theory and strings

A facilities design algorithm is developed based upon such graph theory concepts as maximal spanning trees and planar graphs. The upper bound to the demands made by closeness ratings is developed from graph theory. The algorithm lends itself to computer solution minimizing the costs of flow between activities. An alternative approach using strings and the list processing capabilities of computers is suggested. Numerical examples are provided given input in the form of the relationship matrix and working through the block plan layout.     

Single process plan scheduling with genetic algorithms

AIn this paper, a genetic algorithm model for scheduling manufacturing resources is developed for the case when there is only one process plan available per job, hence there is no routeing flexibility. The scheduling objectives considered are minimizing the makespan and mean flow time. Genetic algorithms design issues are discussed and the working of the employed genetic operators is explained in detail. Parameters for the genetic algorithms used for single process plan scheduling SPPS problems are set through extensive experimentation. Finally, the genetic algorithms approach is compared with several other approaches in terms of optimality of solution and computAuthors: ing time. It was observed that in most cases the genetic algorithms approach performed better than other approaches both in terms of finding an optimal or near optimal solution as well as computing time.     

大规模灾害中基于聚类的医疗物资联合运送优化

应急响应中,往往出现救援物资供应节点与需求节点距离太远、关键道路损毁导致难以及时通过车辆运送物资到灾区等情景,此时直升飞机逐渐被用来运送关键应急资源（如医疗物资及医护人员）。然而,大规模灾害中难以使用直升飞机运送医疗物资到每个医疗救助点,通常考虑灾民的聚集性选择一定数量的应急中转点,以接收直升飞机运送的医疗物资,之后采用车辆运送物资到其覆盖的医疗救助点。针对该问题,提出一种基于聚类的两阶段医疗物资联合运输方法：第一阶段根据医疗救助点分布,采用模糊C-均值算法（FCM）进行应急中转点选择和医疗救助点划分,并针对FCM划分中存在的剩余容量不均衡问题,考虑容量约束提出一种改进划分方法（FCMwCC）,构建“直升飞机-车辆”医疗物资联合运输网络结构;第二阶段建立基于聚类的运送路线优化模型,确定从应急中转点到医疗救助点的具体运送路线。数值实验验证了提出方法和算法的有效性。     

Online integrated allocation of berths and quay cranes in container terminals with 1-lookahead

This paper studies an online over-list model of the integrated allocation of berths and quay cranes (QCs) in container terminals with 1-lookahead ability. The objective is to minimize the maximum completion time of container vessels, i.e., the makespan. We focus on two different types of vessels, three berths and a small number of QCs in the hybrid berth layout, with 1-lookahead ability. We propose a \({{(1 + \sqrt{2} )/2}}\)-competitive algorithm for the case with four cranes, a 5/4-competitive algorithm for the case with five cranes and a 4/3-competitive algorithm for the case with six cranes, respectively. All of the algorithms are proved to be optimal.     

A simple linear time approximation algorithm for multi-processor job scheduling on four processors

Multiprocessor job scheduling problem has become increasingly interesting, for both theoretical study and practical applications. Theoretical study of the problem has made significant progress recently, which, however, seems not to imply practical algorithms for the problem, yet. Practical algorithms have been developed only for systems with three processors and the techniques seem difficult to extend to systems with more than three processors. This paper offers new observations and introduces new techniques for the multiprocessor job scheduling problem on systems with four processors. A very simple and practical linear time approximation algorithm of ratio bounded by 1.5 is developed for the multi-processor job scheduling problem P ₄|fix|C _max, which significantly improves previous results. Our techniques are also useful for multiprocessor job scheduling problems on systems with more than four processors.     

Real-time scheduling and control of one-of-a kind production

Due to the great diversity of product types in one-of-a-kind production (OKP), the production scheduling and control in OKP is much more difficult than production scheduling and control of other production systems, e.g. mass production and batch production. Hence, the production efficiency in OKP companies is relatively lower. To improve productivity in OKP, a dynamic hierarchy production control system is presented. Using this control structure, a production system in an OKP company can be flexibly organized or re-organized according to the structure of a customized product (or an OKP product). Production synchronizing and scheduling algorithms for OKP shop floor production control are presented. Using these algorithms, a cybernetic model can be developed for shop floor control in OKP. The algorithms are applied to two alternate production scheduling goals in OKP, namely ASAP (as soon as possible) production and JIT (just in time) production.     

Multi-objective multi-verse optimiser for integrated two-sided assembly sequence planning and line balancing

Research in assembly optimisation is presently inclined towards integrative measures. Several benefits of simultaneously optimised Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) have been highlighted by researchers to have better solution quality, shorter time-to-market, and minimalised error during planning. Recently, several efforts have been made to realise integrated assembly optimisation. However, none of the published research considered the two-sided assembly line problem. This paper presents an integrated ASP and ALB optimisation in a two-sided assembly environment (2S-ASPLB), which is mainly adopted in automotive assembly process. In this study, the 2S-ASPLB problem was formulated and optimised using Multi-Objective Multi-Verse Optimiser (MOMVO) by considering line efficiency, reorientation penalty, and tool change as the optimisation objectives. The computational experiments were conducted in a few stages, beginning with the identification of the best decoding approach for 2S-ASPLB. Next, the best MOMVO coefficient was studied, followed by comparing MOMVO performance with well-established multi-objective optimisation algorithms. Finally, a case study problem was presented to demonstrate applicability of the proposed model and algorithm in real-life problem. The results indicated that the priority factor (PF) decoding approach had better performance compared with others. Meanwhile, in comparison with well-established algorithms, MOMVO performed better in convergence and solution distribution. The case study results indicated the applicability of proposed 2S-ASPLB model and algorithm to improve line efficiency in assembly line. The main contribution of the research is a new 2S-ASPLB model and optimisation scheme, which can assist manufacturer in designing better assembly layout.