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Decision support for build-to-order supply chain management through multiobjective optimization
This paper aims to identify the gaps in decision-making support based on
multiobjective optimization for build-to-order supply chain management (BTOSCM).
To this end, it reviews the literature available on modelling build-to-order
supply chains (BTO-SC) with the focus on adopting multiobjective optimization
(MOO) techniques as a decision support tool. The literature has been classified based
on the nature of the decisions in different part of the supply chain, and the key
decision areas across a typical BTO-SC are discussed in detail. Available software
packages suitable for supporting decision making in BTO supply chains are also
identified and their related solutions are outlined. The gap between the modelling and
optimization techniques developed in the literature and the decision support needed in
practice are highlighted and future research directions to better exploit the decision
support capabilities of MOO are proposed
Recommended from our members
Decision support for build-to-order supply chain management through multiobjective optimization
This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF
Supply Chain Management in the Life Science Sector: Does Trust Play a Role?
Supply chain management has emerged as cross functional, cross company concept to improve coordination of entire value chains through coordinated actions of all companies in the value chain. It has received a major push from the availability of Internet-based information and communication technologies. The conditions in certain sectors are favorable for a realization of chain wide supply chain management. In other sectors, however, conditions are more complex and companies and value chains still struggle to exploit the potentials from supply chain management, in particular when it comes to cross enterprise coordination. This paper takes a complex supply network as example and discusses improvement potentials from supply chain management and developments in their implementation as well as barriers to the realization of chain wide supply chain management.supply chain management, trust, life science sector, Agribusiness, Industrial Organization,
Designing Enterprise Resources Planning Application for Integrating Main Activities in a Simulator Model of SCM Network Distribution
Collaborative supply chain is a specific topic in supply chain management and studied by
industrial engineering students in supply chain management course. Unfortunately, conventional
learning media cannot explain the phenomenon of collaborative supply chain to the students. This study
aimed to design a dynamic learning media so that inter-company collaboration and information sharing
on the activities of Supply Chain entities can be explained effectively to the students. The problem was
solved using 3 (three) steps. First, the distribution network was described using mock up. It consists of
miniature trucks, miniature network and miniature of the manufacturer-distributor-retailer embedded
with tag and reader of RFID. Second, the Enterprise Resources Planning application was developed for
supporting business activities. Third, we developed the integrator consists of monitor’s user interface
and practice modules. The result of the research - an SCM-Simulator – will be able to improve learning
skills of industrial engineering graduates, especially abilities to identify, formulate, and solve the
activities of tactical plan & operational routines of Supply Chain entities. However, distribution module
designed is for limited scale laboratory study of simple objects.
Keywords: Distribution Network, Enterprise Resource Planning, Industrial Engineering Education,
SCM Simulator,and Learning Media
Models for supply chain negotiation in collaborative relationships
Nowadays, firms are increasingly building collaborative relationships with their partners in order to improve the global performance of the supply chain in which they are involved. Such collaborative relationships require information exchange or share and negotiation. In this paper, we first formalize some practices of collaboration from case studies of the aeronautical area then suggest some models for negotiation, allowing a supply chain member to publish hidden constraints and share risks/costs in order to achieve a win-win situation
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