A price-directed decomposition approach for solving large-scale capacitated part-routing problems

We consider the problem of planning the production steps of several parts through a manufacturing system with both process and routing flexibilities. The problem is formulated as a network flow-based linear programming model which seeks to minimise the total material handling, production, and outsourcing costs subject to satisfying all the part demands and not exceeding any of the machine capacity limits. We develop a price-directed decomposition-based approach that exploits the special structure of the model in order to solve it. An extensive computation experiment is carried out in order to gain some insights into the impacts of flexibility in the manufacturing system on the optimal decision and cost, and to test the efficiency of the procedure in handling large scale problems.     

Design of cellular manufacturing system with quasi-dynamic dual resource using multi-objective GA

A new concept is presented in this paper of quasi-dynamic cell formation for the design of a cellular manufacturing system, based on analysing the fact that static and dynamic cell formation could not reflect the real situation of a modern cellular manufacturing system. Further, workforce resources are integrated into quasi-dynamic cell formation and thus a quasi-dynamic dual-resource cell-formation problem is proposed. For solving this problem, this paper first establishes a non-linear mixed integer programming model, where inter-cell and intra-cell material cost, machine relocation cost, worker operation time, loss in batch quality and worker salary are to be minimised. Then, a multi-objective GA is developed to solve this model. Finally, a real life case study is conducted to validate the proposed model and algorithm. The actual operation results show that the case enterprise significantly decreases its material handling cost and workforce number and obviously increases its product quality after carrying out the obtained scheme.     

A two-phase procedure for duplicating bottleneck machines in a linear layout,cellular manufacturing system

We discuss a two-phase procedure for duplicating bottleneck machines in a cellular manufacturing system. Given a preliminary solution by a clustering technique, the first phase solves a cellular layout problem in which it assigns machine-cells to locations to minimize the total inter-cell material handling costs that result from the bottleneck parts. The purpose of this phase is to find an optimal linear layout of cells. The second phase finds the bottleneck machines that need to be duplicated to minimize the costs. A binary (integer) linear programming model is developed in this phase to minimize the total duplication costs and material handling costs (if not duplicated). Finally, a decision is made as to whether a solution with bottleneck machines, or duplication of bottleneck machines to avoid the bottleneck problem is to be accepted. An example is demonstrated to show how such a bottleneck problem in cellular manufacturing is solved.     

A genetic algorithm and queuing theory based methodology for facilities layout problem

Facilities layout, being a significant contributor to manufacturing performance, has been studied many times over the past few decades. Existing studies are mainly based on material handling cost and have neglected several critical variations inherent in a manufacturing system. The static nature of available models has reduced the quality of the estimates of performance and led to not achieving an optimal layout. Using a queuing network model, an established tool to quantify the variations of a system and operational performance factors including work-in-process (WIP) and utilisation, can significantly help decision makers in solving a facilities layout problem. The queuing model utilised in this paper is our extension to the existing models through incorporating concurrently several operational features: availability of raw material, alternate routing of parts, effectiveness of a maintenance facility, quality of products, availability of processing tools and material handling equipment. On the other hand, a queuing model is not an optimisation tool in itself. A genetic algorithm, an effective search process for exploring a large search space, has been selected and implemented to solve the layout problem modelled with queuing theory. This combination provides a unique opportunity to consider the stochastic variations while achieving a good layout. A layout problem with unequal area facilities is considered in this paper. A good layout solution is the one which minimises the following four parameters: WIP cost, material handling cost, deviation cost, and relocation cost. Observations from experimental analysis are also reported in this paper. Our proposed methodology demonstrates that it has a potential to integrate several related decision-making problems in a unified framework.     

Economic design of unit load-based FMSs employing AGVs for transport

A methodology to economically configure an automated guided vehicle based flexible manufacturing system (FMS) in terms of machine and material handling requirements is presented. The procedure uses the concept of simultaneous design to determine the number of machines required at each workstation in the FMS and the number of automated guided vehicles required to service the material handling needs of the system. The technique integrates decisions on machine requirements, vehicle requirement, and vehicle/container carrying capacity into a single cost model. Solution to the model automatically yields the best resource configuration for the shop that achieves the set production target while minimizing total manufacturing cost. A hybrid algorithm that combines numerical search, simulation, and statistical analysis is employed for solving the problem. The application of the design procedure is demonstrated with an example problem. Sensitivity analysis on machine and vehicle requirements due to changes in job attributes and unit transport quantities are also performed.     

The optimal design of flexible manufacturing systems

The optimal design and control of flexible manufacturing systems is essential to minimize operating costs and enhance productivity. We present a hybrid mathematical model of a flexible manufacturing system as a closed network of queues for which the optimal cost effective system configuration is determined by a. partial implicit enumeration algorithm. The optimal configuration of both reliable and unreliable flexible manufacturing systems are considered.     

New Tabu search heuristics for the dynamic facility layout problem

A manufacturing facility is a dynamic system that constantly evolves due to changes such as changes in product demands, product designs, or replacement of production equipment. As a result, the dynamic facility layout problem (DFLP) considers these changes and is defined as the problem of assigning departments to locations during a multi-period planning horizon such that the sum of the material handling and re-arrangement costs is minimised. In this paper, three tabu search (TS) heuristics are presented for this problem. The first heuristic is a simple TS heuristic. The second heuristic adds diversification and intensification strategies to the first, and the third heuristic is a probabilistic TS heuristic. To test the performances of the heuristics, two sets of test problems from the literature are used in the analysis. The results show that the second heuristic out-performs the other proposed heuristics and the heuristics available in the literature.     

Unequal-area,fixed-shape facility layout problems using the firefly algorithm

In manufacturing industries, the facility layout design is a very important task, as it is concerned with the overall manufacturing cost and profit of the industry. The facility layout problem (FLP) is solved by arranging the departments or facilities of known dimensions on the available floor space. The objective of this article is to implement the firefly algorithm (FA) for solving unequal-area, fixed-shape FLPs and optimizing the costs of total material handling and transportation between the facilities. The FA is a nature-inspired algorithm and can be used for combinatorial optimization problems. Benchmark problems from the previous literature are solved using the FA. To check its effectiveness, it is implemented to solve large-sized FLPs. Computational results obtained using the FA show that the algorithm is less time consuming and the total layout costs for FLPs are better than the best results achieved so far.     

Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm

In this paper, an integrated mathematical model of multi-period cell formation and part operation tradeoff in a dynamic cellular manufacturing system is proposed in consideration with multiple part process route. This paper puts emphasize on the production flexibility (production/subcontracting part operation) to satisfy the product demand requirement in different period segments of planning horizon considering production capacity shortage and/or sudden machine breakdown. The proposed model simultaneously generates machine cells and part families and selects the optimum process route instead of the user specifying predetermined routes. Conventional optimization method for the optimal cell formation problem requires substantial amount of time and memory space. Hence a simulated annealing based genetic algorithm is proposed to explore the solution regions efficiently and to expedite the solution search space. To evaluate the computability of the proposed algorithm, different problem scenarios are adopted from literature. The results approve the effectiveness of the proposed approach in designing the manufacturing cell and minimization of the overall cost, considering various manufacturing aspects such as production volume, multiple process route, production capacity, machine duplication, system reconfiguration, material handling and subcontracting part operation.     

Facility layout optimization using simulation and genetic algorithms

Traditionally, the objective of a facility layout problem has been to minimize the material handling cost of the manufacturing system. While it is important to reduce the amount of material handling, the traditional methods do not address the actual time at which the material is transported. In today's short cycle time production environments, the timing of material movement may have a bigger impact on the productivity of the system than its cost. In this paper, a facility layout optimization technique is presented that takes into consideration the dynamic characteristics and operational constraints of the system as a whole, and is able to solve the facility layout design problem based on a system's performance measures, such as the cycle time and productivity. Each layout solution is presented in the form of a string that is suitable for analysis by a genetic algorithm technique. These solutions are then translated into simulation models by a specially designed automated simulation model generator. Genetic algorithms are used to optimize the layout for manufacturing effectiveness while simulation serves as a system performance evaluation tool. Combined with a statistical comparison technique to reduce the simulation burden, the test results demonstrate that the proposed approach overcomes the limitations of traditional layout optimization methods and is capable of finding optimal or near optimal solutions.     

Solving the multiple platforms configuration problem

The focus of manufacturing has been shifting from mass production to mass customization and producers are seeking ways to reduce production costs, still offering a competitive basket of products. One approach for implementing mass customization is to develop or produce products based on platform architecture. Variant products make use of the product platform as the starting point and then add or remove components to change features of the base product. This allows the manufacturer to offer the variety of products that meet market demands without developing each product independently. In this paper, we propose multiple platforms for the production of a given product family while minimizing the overall production cost. The methodology considers the demand for each product variant, with the decision variables as the optimal number of platforms, optimal configuration of each platform, and assignment of the products to the platforms. The problem is formulated as a mixed integer program, and both the optimal formulation and an evolutionary strategy based on Genetic Algorithm are presented. The approach is illustrated with an example from a family of cordless drills.     

Joint optimization of a flow-shop group scheduling with sequence dependent set-up times and skilled workforce assignment

Flow-shop sequence-dependent group scheduling (FSDGS) problem has been extensively investigated in the literature also due to many manufacturers who implemented the concept of group technology to reduce set-up costs, lead times, work-in-process inventory costs, and material handling costs. On the other hand, skilled workforce assignment (SWA) to machines of a given shop floor may represent a key issue for enhancing the performance of a manufacturing system. As the body of literature addressing the group scheduling problems ignored up to now the effect of human factor on the performance of serial manufacturing systems, the present paper moves in that direction. In particular, an M-machine flow-shop group scheduling problem with sequence-dependent set-up times integrated with the worker allocation issue has been studied with reference to the makespan minimization objective. First, a Mixed Integer Linear Programming model of the proposed problem is reported. Then, a well-known benchmark arisen from the literature is adopted to carry out an extensive comparison campaign among three properly developed metaheuristics based on a genetic algorithm framework. Once the best procedure among those tested is selected, it is compared with an effective optimization procedure recently proposed in the field of FSDGS problems, being this latter properly adapted to run the SWA issue. Finally, a further analysis dealing with the trade-off between manpower cost and makespan improvement is proposed.     

Inventory-shortage driven optimisation for product configuration variation

Inventory control is a critical problem in manufacturing systems. Inventory shortage significantly affects system productivity, while excessive stocks increase the operation cost. It is difficult to avoid fully inventory shortage under mass customisation manufacturing based on product configuration. In this paper, we propose a new approach for inventory-shortage driven optimisation of dynamic product configuration variation to meet the requirements of product configuration change and find suitable combination of parts by considering cost, lead-time and inventory variation. The multi-objective optimisation model uses a multi-objective genetic algorithm and adds impact cost, lead-time and inventory factors to the normal configuration optimisation model. An industrial case study demonstrates the practicality and effectiveness of the proposed approach. By means of this research, valid solutions for configuration variation are available to the decision makers.     

A simulated annealing algorithm based on a closed loop layout for facility layout design in flexible manufacturing systems

Facility layout design problems in flexible manufacturing systems (FMS) differ from traditional facility design problems and are more difficult to solve because there are more constraints that must be considered (i.e., cell shape, cell orientation, pick-up and drop-off point positions). The focus of this paper is on the closed loop type layout, which is based on a predetermined layout pattern. This layout pattern is commonly found in manufacturing settings since it requires a simplified material handling system configuration and since it facilitates a modular and expandable layout structure. The open-field type layout problem, where there is no predetermined layout pattern, may potentially have a more efficient configuration, since there are fewer restrictions. However, this problem is more difficult to solve and may result in configurations that are not desirable due to the lack of structure or modularity. The procedure developed in this paper improves the efficiency of the closed loop configuration by changing the rectangular shape of the loop to different sizes. In many cases, the resulting closed loop layout proves to be as efficient as the open field layout. A simulated annealing procedure (SA-CL) is used to search for the configuration that minimizes the total material handling costs. A comparison of the results with existing methods indicates that, based on solution quality and computational time, the SA-CL offers a favourable alternative for efficient layout design.     

Book review of Global Strategic Management,by P. Lasserre,Palgrave Macmillan,Basingstoke, 2003, xx + 454 pp., £24.99, softcover (ISBN 0 333 79375 7)

This paper considers the simultaneous scheduling of material handling transporters (such as automatic guided vehicles or AGVs) and manufacturing equipment (such as machines and workcentres) in the production of complex asembled product. Given the shipping schedule for the end-items, the objective of the integrated problem is to minimize the cumulative lead time of the overall production schedule (i.e. total makespan) for on-time shipment, and to reduce material handling and inventory holding costs on the shop-floor. The problem of makespan minimization is formulated as a transportation integrated scheduling problem, which is NP-hard. For industrial size problems, an effective heuritsic is developed to simultaneouly schedule manufacturing and material handling operations by exploting the critical path of an integrated operation network. The performance of the proposed heuristic is evaluated via extensive numerical studies and compared with the traditional sequential scheduling approach. The superiority of the integrated heuristic is well documented.     

Fuzzy approach to the robust facility layout in uncertain production environments

The proposed method approaches the problem of the optimal facility layout using fuzzy theory. The optimal layout is a robust layout that minimizes the total material handling cost, when the product market demands are uncertain variables, which are defined as fuzzy numbers. Since each department has a limited production capacity, not all possible combinations, deriving from each product's market demand, are taken into account because some combination could exceed the overall department's productivity. Therefore, the optimal solution results by solving a 'constrained' fuzzy optimization problem, in which the fuzzy material handling costs corresponding to the layouts are evaluated, and a ranking method, which considers the grade of pessimism of the decision maker, is established to determine the optimal layout.     

Use of activity-based costing and economic value analysis for the justification of capital investments in automated material handling systems

This paper develops a two-stage method for the justification of investment in modern material handling systems. The underlying approach places heavy emphasis on the use of cost avoidance data quantified by activity-based costing systems. The first stage collects the life-cycle costs and benefits resulting from the reconfiguration of material handling systems in manufacturing facilities. A recently developed software package for process modelling and management is employed to capture the characteristics of material handling activities and to derive accurate applied cost rates for each activity and material handling system combination. These activity-related cost data as well as various opportunity costs are incorporated in a case-specific, investment decision model that constitutes the second stage of the method. The model performs an Economic Value Analysis for each material handling alternative. In doing so, it offers a sound basis for economic comparison of different systems. A case study illustrates the merit of our two-stage method in decision making by placing an accurate and reliable economic value on the transition from manual to automated material handling in a manufacturing facility. The use of activity-based costs reverses the decision of sustaining the 'status quo' supported by a traditional investment justification approach restricted to solely labour cost reductions     

Solving cell formation and task scheduling in cellular manufacturing system by discrete bacteria foraging algorithm

We consider a joint decision model of cell formation and task scheduling in cellular manufacturing system under dual-resource constrained (DRC) setting. On one hand, machines and workers are multi-functional and/or multi-skilled, and they are grouped into workstations and cells. On the other hand, there is a processing sequence among operations of the parts which needs to be dispatched to the desirable workstations for processing. Inter-cell movements of parts can reduce the processing times and the makespan but will increase the inter-cell material handling costs. The objective of the problem is to minimise the material handling costs as well as the fixed and operating costs of machines and workers. Due to the NP-hardness of the problem, we propose an efficient discrete bacteria foraging algorithm (DBFA) with elaborately designed solution representation and bacteria evolution operators to solve the proposed problem. We tested our algorithm using randomly generated instances with different sizes and settings by comparing with the original bacteria foraging algorithm and a genetic algorithm. Our results show that the proposed DBFA has better performance than the two compared algorithms with the same running time.     

CVaR准则下季节性产品市场运作策略

研究了风险规避型零售商在面对季节性产品随机市场需求受销售价格和广告费用共同影响时的最优运作策略。通过乘法需求形式将销售价格、广告费用对需求的影响引入报童问题中,以CVaR作为风险度量准则,建立了风险规避型零售商销售价格、广告费用及订货量联合决策的随机模型;并进一步揭示了零售商的风险规避程度对其最优运作策略的影响;通过数值实例对模型的求解过程和理论结果进行了验证分析。研究结果为季节性产品零售商市场运作策略的制定提供了一定的参考。     

Designing group layout of unequal-area facilities in a dynamic cellular manufacturing system with variability in number and shape of cells

This paper presents a new mixed-integer non-linear programming model for designing the group layout (GL) of unequal-area facilities in a cellular manufacturing system (CMS) under a dynamic environment. There are some features that make the presented model different from the previous studies. These include: (1) manufacturing cells with variable numbers and shapes, (2) machine depot keeping idle machines, (3) machines of unequal-areas, (4) manufacturing cells with rectangle regular shapes established on the continuous shop floor and (5) integration of cell formation and GL as interrelated decisions involved in the design of a CMS in a dynamic environment. The objective function is to minimises the total costs of intra- and inter-cell material handling, machine overhead, machine relocation, machine processing, purchasing machines and forming cells. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. The performance of this model is illustrated by two numerical examples. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in comparison to the classical genetic algorithm (GA). The obtained results show that the quality of the solutions obtained by SA is better than GA.