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| 2. |
- Aslam, Tehseen, et al.
(author)
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Agent-based Simulation and Simulation-based Optimisation for Supply Chain Management
- 2010
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In: Enterprise Networks and Logistics for Agile Manufacturing. - London : Springer London. - 9781849962438 - 9781849962445 ; , s. 227-247
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Book chapter (other academic/artistic)abstract
- Agent-based simulation (ABS) represents a paradigm in the modelling and simulation of complex and dynamic systems distributed in time and space. Since manufacturing and logistics operations are characterised by distributed activities as well as decision making - in both time and in space - and can be regarded as complex, the ABS approach is highly appropriate for these types of systems. The aim of this chapter is to present a new framework of applying ABS and simulation-based optimisation techniques to supply chain management, which considers the entities (supplier, manufacturer, distributor and retailer) in the supply chain as intelligent agents in a simulation. This chapter also gives an outline on how these agents pursue their local objectives/goals as well as how they react and interact with each other to achieve a more holistic objective(s)/goal(s).
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| 3. |
- Aslam, Tehseen, 1981-
(author)
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Analysis of manufacturing supply chains using system dynamics and multi-objective optimization
- 2013
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Doctoral thesis (other academic/artistic)abstract
- 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. Hence, due to the multiple performance measures, supply chain decision making is much more complex than treating it as a single objective optimization problem. Thus, the aim of the doctoral thesis is to address the supply chain optimization problem within a truly Pareto-based multi-objective context and utilize knowledge extraction techniques to extract valuable and useful information from the Pareto optimal solutions. By knowledge extraction, it means to detect hidden interrelationships between the Pareto solutions, identify common properties and characteristics of the Pareto solutions as well as discover concealed structures in the Pareto optimal data set in order to support managers in their decision making. This aim is addressed through the SBO-framework where the simulation methodology is based on system dynamics (SD) and the optimization utilizes multi-objective optimization (MOO). In order to connect the SD and MOO software, this doctoral thesis introduced a novel SD and MOO interface application which allow the modeling and optimization applications to interact. Additionally, this thesis work also presents a novel SD-MOO methodology that addresses the issue of curse off dimensionality in MOO for higher dimensional problems and with the aim to execute supply chain SD-MOO in a computationally cost efficient way, in terms of convergence, solution intensification and accuracy of obtaining the Pareto-optimal front for complex supply chain problems. In order to detect evident and hidden structures, characteristics and properties of the Pareto-optimal solutions, this work utilizes Parallel Coordinates, Clustering and Innovization, which are three different types of tools for post-optimal analysis and facilitators of discovering and retrieving knowledge from the Pareto-optimal set. The developed SD-MOO interface and methodology are then verified and validated through two academic case studies and a real-world industrial application case study. While not all the insights generated in these application studies can be generalized for other supply-chain systems, the analysis results provide strong indications that the methodology and techniques introduced in this thesis are capable to generate knowledge to support academic SCM research and real-world SCM decision making, which to our knowledge cannot be performed by other methods.
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| 4. |
- Aslam, Tehseen, et al.
(author)
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Combining system dynamics and multi-objective optimization with design space reduction
- 2016
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In: Industrial management & data systems. - : Emerald Group Publishing Limited. - 0263-5577 .- 1758-5783. ; 116:2, s. 291-321
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Journal article (peer-reviewed)abstract
- Purpose The purpose of this study is to introduce an effective methodology for obtaining Pareto-optimal solutions, when combining System Dynamics (SD) and Multi-Objective Optimization (MOO) for supply chain problems.Design/methodology/approach This paper proposes a new approach that combines SD and MOO within a simulation-based optimization framework to generate the efficient frontier that supports decision- making in SupplyChain Management (SCM). It also addresses the issue of the curse of dimensionality, commonly found in practical optimization problems, through design space reduction.Findings The integrated MOO and SD approach has been shown to be very useful in revealing how the decision variables in the Beer Game affect the optimality of the three common SCM objectives, namely, the minimization of inventory, backlog, and the bullwhip effect. The results of the in-depth Beer Game study clearly show that these three optimization objectives are in conflict with each other, in the sense that a supply chain manager cannot minimize the bullwhip effect without increasing the total inventory and total backlog levels.Practical implications Having a methodology that enables the effective generation of optimal trade-off solutions, in terms of computational cost, time, as well as solution diversity and intensification, not only assists decision makers to make decisions on time, but also presents a diverse and intense solution set to choose from.Originality/value This paper presents a novel supply chain MOO methodology that helps to find Pareto-optimal solutions in a more effective manner. In order to do so, the methodology tackles the so-called curse of dimensionality, by reducing the design space and focusing the search of the optimization to regions of interest. Together with design space reduction, it is believed that the integrated SD and MOOapproach can provide an innovative and efficient method for the design and analysis of manufacturing supply chain systems in general.
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| 5. |
- Aslam, Tehseen, 1981-, et al.
(author)
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Education of the Future : Learnings and Experiences from Offering Education to Industry Professionals
- 2022
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In: SPS2022. - Amsterdam; Berlin; Washington, DC : IOS Press. - 9781643682686 - 9781643682693 ; , s. 665-676
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Conference paper (peer-reviewed)abstract
- Digitalization is forcing the industry to rethink current practices in all business domains, pushing for a digital transformation of business and operations at a high rate and, thus, paving the way for new business models and making others redundant. For small and medium-sized companies (SME), in particular, it is an enormous challenge to keep up with the pace of technological development. Several initiatives have argued the industry’s need for continuous digitalization, innovation, transformation ability, and future skills and competencies development. However, the advancement of the Swedish industry in this area has been uneven, where larger organizations have begun their digital transformation journey to some extent, but SMEs risk falling behind. In addition to the technological transformation, the challenges regarding the industries’ skills supply need to be solved, where a workforce with the right competencies, knowledge, and skill sets are equally, if not more, important for remaining competitive. One of the key elements to face these challenges in the companies will be to recruit knowledgeable employees or re-skill the existing ones. Efficient access to relevant knowledge and skills is still a major concern for companies that will surely affect their competitiveness for a long time to come. This paper elaborates on the opportunities and challenges that Swedish universities face in the context of lifelong learning and education for industry professionals. The paper presents results and experiences gained from a lifelong learning project for industry professionals at the University of Skövde in collaboration with ten industry partners. The results from the project show that in addition to pedagogical methods, current structures and policies within academia need to be further developed to effectively serve industry professionals. The paper also presents a concept of education for industry professionals in the lifelong learning context based on the results and experience gained from the project.
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| 6. |
- Aslam, Tehseen, et al.
(author)
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Integrating system dynamics and multi-objective optimisation for manufacturing supply chain analysis
- 2014
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In: International Journal of Manufacturing Research. - : InderScience Publishers. - 1750-0605. ; 9:1, s. 27-57
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Journal article (peer-reviewed)abstract
- The aim of this paper is to address the dilemma of supply chain management (SCM) within a truly Pareto-based multi-objective context. This is done by introducing an integration of system dynamics and multi-objective optimisation. An extended version of the well-known pedagogical SCMproblem, the Beer Game, originally developed at MIT since the 1960s, has been used as the illustrative example. As will be discussed in the paper, the integrated multi-objective optimisation and system dynamics model has been shown to be very useful for revealing how the parameters in the Beer Game affect the optimality of the three common SCM objectives, namely, the minimisation of inventory cost, backlog cost, and the bullwhip effect.
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| 7. |
- Aslam, Tehseen, et al.
(author)
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Multi-objective Optimisation in Manufacturing Supply Chain Systems Design : A Comprehensive Survey and New Directions
- 2011
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In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. - London : Springer London. - 9780857296177 - 9780857296528 ; , s. 35-70
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Book chapter (peer-reviewed)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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| 9. |
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| 10. |
- Aslam, Tehseen, et al.
(author)
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Multi-Objective Optimization for Supply Chain Management : A Literature Review and New Development
- 2010
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In: SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems. - : The Hong Kong Polytechnic University. - 9789623676977 - 9789623676960 ; , s. Article number 5681724-
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Conference paper (peer-reviewed)abstract
- Research regarding supply chain optimization has been performed for a long time. However, it’s only in the last decade that the research community has started to investigate multi-objective optimization 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 paper, we present a literature review of existing multi-objective optimization applications, both analytical-based and simulation-based, in supply chain management publications. Based on the literature review, the need for research in a multi-objective and multi-level optimization framework for supply chain management is proposed. Such a framework considers not only the optimization of the overall supply chain, but also for each entity within the supply chain, in a multi-objective optimization context.
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