| 1. |
- Aslam, Tehseen, et al.
(författare)
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Multi-objective Optimisation in Manufacturing Supply Chain Systems Design : A Comprehensive Survey and New Directions
- 2011
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Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - London : Springer London. - 9780857296177 - 9780857296528 ; , s. 35-70
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Bokkapitel (refereegranskat)abstract
- Research regarding supply chain optimisation has been performed for a long time. However, it is only in the last decade that the research community has started to investigate multi-objective optimisation for supply chains. Supply chains are in general complex networks composed of autonomous entities whereby multiple performance measures in different levels, which in most cases are in conflict with each other, have to be taken into account. In this chapter, we present a comprehensive literature review of existing multi-objective optimisation applications, both analytical-based and simulation-based, in supply chain management publications. Later on in the chapter, we identify the needs of an integration of multi-objective optimisation and system dynamics models, and present a case study on how such kind of integration can be applied for the investigation of bullwhip effects in a supply chain.
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| 2. |
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| 3. |
- Li, Weidong, et al.
(författare)
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Intelligent Optimisation for Integrated Process Planning and Scheduling
- 2011
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Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - London : Springer London. - 9780857296177 - 9780857296528 ; , s. 305-324
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Bokkapitel (refereegranskat)abstract
- Traditionally, process planning and scheduling were performed sequentially, where scheduling was executed after process plans had been generated. Considering the fact that the two functions are usually complementary, it is necessary to integrate them more tightly so that the performance of a manufacturing system can be improved greatly. In this chapter, a multi-agent-based framework has been developed to facilitate the integration of the two functions. In the framework, the two functions are carried out simultaneously, and an optimization agent based on evolutionary algorithms is used to manage the interactions and communications between agents to enable proper decisions to be made. To verify the feasibility and performance of the proposed approach, experimental studies conducted to compare this approach and some previous works are presented. The experimental results show the proposed approach has achieved significant improvement.
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| 4. |
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| 5. |
- Ng, Amos H. C., et al.
(författare)
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Simulation-Based Innovization Using Data Mining for Production Systems Analysis
- 2011
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Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - London : Springer London. - 9780857296177 - 9780857296528 ; , s. 401-429
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Bokkapitel (refereegranskat)abstract
- This chapter introduces a novel methodology for the analysis and optimization of production systems. The methodology is based on the innovization procedure, originally introduced for unveiling new and innovative design principles in engineering design problems. Although the innovization method is based on multi-objective optimization and post-optimality analyses of optimised solutions, it stretches the scope beyond an optimization task and attempts to discover new design/operational rules/principles relating to decision variables and objectives, so that a deeper understanding of the problem can be obtained. By integrating the concept of innovization with discrete-event simulation and data mining techniques, a new set of powerful tools can be developed for general systems analysis, particularly suitable for production systems. The uniqueness of the integrated approach proposed in this chapter lies on applying data mining to the data sets generated from simulation-based multi-objective optimization, in order to automatically or semi-automatically discover and interpret the hidden relationships and patterns for optimal production systems design/reconfiguration.
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| 6. |
- Pehrsson, Leif, et al.
(författare)
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Multi-objective Production Systems Optimisation with Investment and Running Cost
- 2011
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Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - London : Springer London. - 9780857296177 - 9780857296528 ; , s. 431-453
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Bokkapitel (refereegranskat)abstract
- In recent years simulation-based multi-objective optimisation (SMO) of production systems targeting e.g., throughput, buffers and work-in-process (WIP) has been proven to be a very promising concept. In combination with post-optimality analysis, the concept has the potential of creating a foundation for decision support. This chapter will explore the possibility to expand the concept of introducing optimisation of production system cost aspects such as investments and running cost. A method with a procedure for industrial implementation is presented, including functions for running cost estimation and investment combination optimisation. The potential of applying SMO and postoptimality analysis, taking into account both productivity and financial factors for decision-making support, has been explored and proven to be very beneficial for this kind of industrial application. Evaluating several combined minor improvements with the help of SMO has opened the opportunity to identify a set of solutions (designs) with great financial improvement, which are not feasible to be explored by using current industrial procedures.
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| 7. |
- Wang, Lihui, et al.
(författare)
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Preface
- 2011
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Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - : Springer London. - 9780857296177 ; , s. v-viii
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 8. |
- Wang, Lihui, et al.
(författare)
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Reconfigurable Facility Layout Design for Job-Shop Assembly Operations
- 2011
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Ingår i: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - London : Springer London. - 9780857296177 - 9780857296528 ; , s. 365-384
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Bokkapitel (refereegranskat)abstract
- Highly turbulent environment of dynamic job-shop operations affects shop-floor layout as well as manufacturing operations. Due to the dynamic nature of layout changes, essential requirements such as adaptability and responsiveness to the changes need to be considered in addition to the cost issues of material handling and machine relocation when reconfiguring a shop floor’s layout. Here, based on the source of uncertainty, the shop-floor layout problem is split into two sub-problems and dealt with by two modules: re-layout and find-route. Genetic algorithm is used where changes cause the entire shop re-layout, while function blocks are utilized to find the best sequence of robots for the new conditions within the existing layout. This chapter reports the latest development to the authors’ previous work.
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| 9. |
- Ölvander, Johan, 1972-, et al.
(författare)
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Multi-objective Optimization of a family of Industrial Robots
- 2011
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Ingår i: <em>Multi-objective Evolutionary Optimisation for Product Design and Manufacturing</em>. - : Springer Verlag. - 9780857296177 ; , s. 189-217
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Bokkapitel (refereegranskat)abstract
- With the increasing complexity and dynamism in today’s product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.
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