A heuristic approach on the facility layout problem based on game theory

Facility layout problems are related to the location of all facilities in a plant. Numerous research works related to facility layout have been published. The applicability of these various existing models may be limited by the fact that they all ignore competitive reactions to one's actions. In addition to external competitors, some internal problems of system such as material handling system design affect layout designs. For considering these effects, some researchers have investigated multi-objective approaches that in most cases lead to the optimisation of a weighted sum of score functions. The poor practicability of such an approach is due to the difficulty of normalising these functions and quantifying the weights. To the extent that competitors do react to a firm's actions and also the facility layout problem considers several conflicting objectives by distinct decision makers in the firm, the existing models may be oversimplifications of reality. In this paper, we modelled such a facility layout problem with conflicting objectives under a duopoly Bertrand competition as a game and solved it with a proposed simulated annealing meta-heuristic. Results obtained from solving some numerical examples confirm the effectiveness of the proposed model for the layout design.     

制约理论之思维流程在某制造企业的应用

按照思维流程的三条逻辑脉络:改变什么,改成什么样,怎样去改.以某制造企业为例说明了TP的五大逻辑关系图:当前现实树、冲突化解图、未来现实树、必备树和转移树的运用过程,以帮助企业发现核心问题,找到解决问题的方案并采取行动最终解决问题.     

Optimizing Transportation Problems with Multiple Objectives

Virtually all models developed for transportation problems have focused upon the optimization of a single objective criterion, namely the minimization of total transportation costs. They have generally neglected or often ignored the multiple conflicting objectives involved in the problem, the priority structure of these objectives, various environmental constraints, unique organizational values of the firm, and bureaucratic decision structures. However, in reality these are important factors which greatly influence the decision process of transportation problems. In this study the goal programming approach is utilized in order to allow for the optimization of multiple conflicting goals while permitting an explicit consideration of the existing decision environment.     

Implementing theory of constraints in a traditional Japanese manufacturing environment: The case of Hitachi Tool Engineering

This research presents a case study of a virtual ‘textbook’ application of the theory of constraints (TOC) in a Japanese tool manufacturing company. Hitachi Tool Engineering uses state-of-the-art technology to design and manufacture cutting tools known as End-mills. The plant described in this study is a classic V-plant and exhibited all of the standard problems of a traditionally managed V-plant, existing within the unique framework of Japanese work culture. Plant management applied the five focusing steps and used the operations strategy tools, including drum-buffer-rope and buffer management, to improve the system. Following the approach recommended by Eli Goldratt, the thinking process tools of current reality tree and evaporating clouds were used to help identify and resolve problems when the implementation encountered major obstacles. While the implementation was a huge success, the devastating effect of a core problem being left unresolved is well documented. The implementation generated significant improvements in work-in-process inventory, production lead time, on-time delivery, productive capacity, inventory turnover, product quality, sales volume, and profitability. Moreover, management has extended the introduction of TOC to the non-manufacturing functions and TOC is becoming the common company culture that bridges four culturally diverse manufacturing plants.     

Cost effective simulation-based multiobjective optimization in the performance of an internal combustion engine

Solving real-life engineering problems can be difficult because they often have multiple conflicting objectives, the objective functions involved are highly nonlinear and they contain multiple local minima. Furthermore, function values are often produced via a time-consuming simulation process. These facts suggest the need for an automated optimization tool that is efficient (in terms of number of objective function evaluations) and capable of solving global and multiobjective optimization problems. In this article, the requirements on a general simulation-based optimization system are discussed and such a system is applied to optimize the performance of a two-stroke combustion engine. In the example of a simulation-based optimization problem, the dimensions and shape of the exhaust pipe of a two-stroke engine are altered, and values of three conflicting objective functions are optimized. These values are derived from power output characteristics of the engine. The optimization approach involves interactive multiobjective optimization and provides a convenient tool to balance between conflicting objectives and to find good solutions.     

Soft constraint handling for a real-world multiobjective energy distribution problem

Real-world optimisation problems usually involve some conflicting objectives and a number of constraints. In such cases, finding a feasible, Pareto-optimal solution poses a demanding challenge. In reality, constraints bear different importance levels to these conflicting objectives. If some constraints are relaxed within an acceptable degree, quality infeasible solutions could be found on the boundary from the infeasible side of the searching region. This paper formulates an energy distribution problem arising from a real-world iron and steel production as a multiobjective optimisation problem. During the course of the optimisation search, this paper attempts to handle certain constraints in a soft manner to find solutions with good balance among objective and constraints violation. Based on the analysis of constraints from the real-world perspective, different tolerance values are defined. The proposed constraint violation degree-based soft handling approach is incorporated into the advanced version of non-dominated sorting genetic algorithm framework, as a case study, to examine the efficiency of the proposed soft constraint handling approach for a real-world energy distribution problem. The proposed approach is also implemented in different ways of constraint handling and tested on some benchmark functions to further demonstrate the performance of soft constraint handling for multiobjective optimisation problems.     

A quality function deployment-based model for materials selection

Materials play a key role during the entire product design and manufacturing phase as a wrongly selected material may often lead to premature product failure causing loss of revenue and repute of the concerned manufacturing organization. While selecting the most suitable material for a specific application, the designers often need a sound and systematic methodology to deal with this problem having multiple candidate alternative choices and conflicting objectives. Most of the previously applied methodologies for material selection have either adopted criteria weights estimated using subjective judgments of the designers or failed to give due emphasis on the voice of the customers to meet their requirements. In this paper, a maiden venture is taken to solve the material selection problems using a quality function deployment (QFD)-based approach that can integrate the voice of the customers for a product with its technical requirements. The applicability and solution accuracy of this QFD-based material selection model is demonstrated with the help of four illustrative examples. To ease out the materials selection decision-making process, a user-friendly software prototype in Visual BASIC 6.0 is also developed.     

Machine-tool selection and operation allocation in FMS: Solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.     

A comparison of alternative kanban control mechanisms. II. Experimental results

This paper continues our study of the design of inventory control policies for serial systems. Using simulation, we compare alternate control policies where a target of mean throughput has to be met under three different objectives - minimize the maximum inventory, minimize the average inventory and minimize the variance of the output - for balanced lines and lines with one bottleneck,

The main objectives of this paper are: (1) to study several objectives not amenable to sample path analysis and (2) to show some sets of conditions and objectives under which Constant-Work-in Progress (CONWIP) is preferred over the traditional kanban mechanism, and vice-versa.     

A shuffled frog-leaping algorithm for flexible job shop scheduling with the consideration of energy consumption

Flexible job shop scheduling problem (FJSP) has been extensively investigated and objectives are often related to time. Energy-related objective should be considered fully in FJSP with the advent of green manufacturing. In this study, FJSP with the minimisation of workload balance and total energy consumption is considered and the conflicting between two objectives is analysed. A shuffled frog-leaping algorithm (SFLA) is proposed based on a three-string coding approach. Population and a non-dominated set are used to construct memeplexes according to tournament selection and the search process of each memeplex is done on its non-dominated member. Extensive experiments are conducted to test the search performance of SFLA and computational results show the conflicting between two objectives of FJSP and the promising advantages of SFLA on the considered FJSP.     

Distance-based consensus method for ABC analysis

A distance-based multi-criteria consensus framework on the concepts of ideal and negative-ideal solutions is presented for the ABC analysis of inventory items. This article demonstrates a way of classifying inventory items using the TOPSIS (‘Technique for Order Preference by Similarity to Ideal Solution’) model. The methodology has been applied in a pharmaceutical company located in the heart of Kolkata, India. The technique takes into account various conflicting criteria having incommensurable units of measurement. Unit cost, lead time, consumption rate, perishability of items and cost of storing of raw materials have been considered for the case study. By using TOPSIS, the items are ranked in categories A, B and C. The suitability, practicability and effectiveness of the TOPSIS method used in ABC classification have been judged using the analysis of variance (ANOVA) technique. A simulation model has been used to compare the proposed model with that of the traditional ABC classification technique.     

Strategies for integrating lead time and customer-order decisions

Make-to-order manufacturers are facing unprecedented challenges to fill their customer orders quickly and to reduce their operating costs. In this paper, we first describe and discuss order taking and lead time quoting practice in a real world make-to-order manufacturing system. We then develop a model for this practical problem to study the conflicting objectives, of delivering customized orders quickly and maximizing expected profit. The primary goal of this paper is to develop a general model for studying the trade-offs and the interrelationships among the following manufacturing performance measures: manufacturing flow times, quoted lead time reliability (earliness and tardiness), throughput (or demand) rates, inventory levels, resource utilization, and expected profits. These and other related managerial issues are explored. Our structural results yield insights into basic choices between filling customer orders quickly and maximizing expected profit.     

Variation-aware clock network buffer sizing using robust multi-objective optimization

Many engineering optimization problems include unavoidable uncertainties in parameters or variables. Ignoring such uncertainties when solving the optimization problems may lead to inferior solutions that may even violate problem constraints. Another challenge in most engineering optimization problems is having different conflicting objectives that cannot be minimized simultaneously. Finding a balanced trade-off between these objectives is a complex and time-consuming task. In this paper, an optimization framework is proposed to address both of these challenges. First, we exploit a self-calibrating multi-objective framework to achieve a balanced trade-off between the conflicting objectives. Then, we develop the robust counterpart of the uncertainty-aware self-calibrating multi-objective optimization framework. The significance of this framework is that it does not need any manual tuning by the designer. We also develop a mathematical demonstration of the objective scale invariance property of the proposed framework. The engineering problem considered in this paper to illustrate the effectiveness of the proposed framework is a popular sizing problem in digital integrated circuit design. However, the proposed framework can be applied to any uncertain multi-objective optimization problem that can be formulated in the geometric programming format. We propose to consider variations in the sizes of circuit elements during the optimization process by employing ellipsoidal uncertainty model. For validation, several industrial clock networks are sized by the proposed framework. The results show a significant reduction in one objective (power, on average 38 %) as well as significant increase in the robustness of solutions to the variations. This is achieved with no significant degradation in the other objective (timing metrics of the circuit) or reduction in its standard deviation which demonstrates a more robust solution.     

The facilities layout problem: a multi-goal approach

This paper presents a combined quantitative and qualitative (subjective) approach to the plant layout problem. The two objectives, which may be conflicting, are minimizing the material handling cost and maximizing a closeness rating measure. A heuristic algorithm is developed which results in a discrete efficient frontier set, including only 'efficient layouts’. By specifying the different weights, or range of weights, for these goals, the 'best’ solution (layout) is generated.     

GRASP with path relinking for a multiple objective sequencing problem for a mixed-model assembly line

This research presents a new application of greedy randomised adaptive search procedure (GRASP) to address a production sequencing problem for mixed-model assembly line in a just-in-time (JIT) production system in two different cases. In the former case, small size sequencing problems are considered and two objectives are presented; minimisation of setups and optimisation of stability of material usage rates. These two objectives are inversely correlated with each other, so simultaneous optimisation of both is challenging. This type of problem is NP-hard. The GRASP, with path relinking, searches for efficient frontier where simultaneous optimisation of number of setups and usage rates is desired. Several test problems are solved via GRASP and its performance is compared to solutions obtained via complete enumeration and simulated annealing (SA), tabu search (TS) and genetic algorithms (GA) approaches from the literature. Experimental results reveal that the GRASP with path relinking provides near-optimal solutions in terms of the two objectives and its ‘average inferiority%’ and ‘average percentile’ performances are superior to that of other heuristics. In the latter case, the goal is to explore varying the emphasis of these two conflicting objectives. Larger sequencing problems are considered and solved via GRASP with path relinking. Its objective function values are compared to the solutions obtained via a SA approach from the literature. Experimental results show that GRASP also provides good performance on large size problems and its percentage improvement is better than that of SA. Overall results also show, however, that the GRASP performs poorly with regard to CPU time.     

基于供应链管理的企业库存优化效果模拟与分析

利用供应链管理的思想,通过对供应链上的企业库存进行优化模拟与分析,揭示了供应链内部信息共享、加快信息流动、缩短订货周期、供应商管理库存(VMI)等是影响供应链管理优化效果的核心因素;通过比较应用供应链管理前后企业库存的变化,说明了供应链管理可以有效平抑库存,缩短供货周期,降低企业成本,提高企业核心竞争力。     

An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers

This paper proposes a multi-objective optimisation algorithm for solving the new multi-objective location-inventory problem (MOLIP) in a distribution centre (DC) network with the presence of different transportation modes and third-party logistics (3PL) providers. 3PL is an external company that performs all or part of a company’s logistics functions. In order to increase the efficiency and responsiveness in a supply chain, it is assumed that 3PL is responsible to manage inventory in DCs and deliver products to customers according to the provided plan. DCs are determined so as to simultaneously minimise three conflicting objectives; namely, total costs, earliness and tardiness, and deterioration rate. In this paper, a non-dominated sorting genetic algorithm (NSGA-II) is proposed to perform high-quality search using two-parallel neighbourhood search procedures for creating initial solutions. The potential of this algorithm is evaluated by its application to the numerical example. Then, the obtained results are analysed and compared with multi-objective simulated annealing (MOSA). It is concluded that this algorithm is capable of generating a set of alternative DCs considering the optimisation of multiple objectives, significantly improving the decision-making process involved in the distribution network design.     

供应链视角下工程材料库存优化研究

目的为了达到节约工程建设行业企业材料管理成本的目的,以常用的2种工程材料钢材和水泥存储于同一仓库且由同一供应商供货的库存管理为研究对象进行研究。方法分析承包商采购材料情形下,供应商和承包商基于合作伙伴关系实现库存信息共享,建立2种材料两级库存联合库存成本优化的数学模型,并通过工程实例,运用粒子群算法求解,验证研究方法的有效性。结果不同的材料订购策略对工程供应链上的材料库存成本影响很大,数学模型可以给出恰当的订购策略,满足系统成本的最低要求,从而节约成本,提升工程供应链的整体竞争力。结论研究成果丰富了工程供应链管理理论、工程材料的库存管理理论,并对工程建设实践中的材料采购有一定的指导意义。     

A COMPARISON OF THREE METHODS FOR GENERATING THE PARETO OPTIMAL SET

This paper describes and compares three approaches to solving design optimization problems with multiple conflicting objectives. The three techniques are described in detail and then applied lo an example which demonstrates how information is accumulated which leads to a logical and efficient multicriteria optimal design. The techniques employed (weighting, noninferior set estimation and constraint methods) ate compared to each other by considering their computational efficiencies and their abilities to produce an approximation of the Pareto optimal set.     

物料采购看板在船用设备企业的应用

根据船舶制造业的特点,通过对原有物料控制方法的分析,找出物料控制方法中存在的问题。运用ABC分析和统计分析的方法确认需要使用看板控制的物料;提出了在物料需求不稳定的情况下计算采购看板数量的方法,通过设计的采购看板系统达到了降低原材料库存的目的。