121,439 research outputs found
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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
Evaluating Government's Policies on Promoting Smart Metering in Retail Electricity Markets via Agent Based Simulation
Burton Optical Company (Cases A & B)
Thesis (M.B.A.)--Boston Universit
Global supply chains of high value low volume products
Imperial Users onl
Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction
The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the base of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution route with and without carbon emissions cost are constructed, and fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, the path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit
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
ICROFS news 2/2009 - newsletter from ICROFS
News from ICROFS:
CORE Organic ERA-net proposal is formulated, FAO side-event was a success, upcoming course in media handling
Articles:
J. Eriksen, M. Askegaard & K. Søegaard: Nitrogen management on large organic daity farms
C. Daugbjerg & K. M. Sønderskov: Organic labelling systems and consumer confidence
G. T. Svendsen: Organic farmers can gain from Green House Gas trade
H. Egelyng: Certified Organic Agriclture: Policy Instrument for Sustainable Development?
M.S. Carter & N. Chirinda: No effect of cropping system on the greenhouse gas N2O
J.H. Ingemann: Economics, Policy, and Organic Agriculture
Brief news:
TP ORganics needs you!, New publication: The World of ORganic Agriculture: Statistics and emerging trends, NJF seminar, Organic farmers bite back!, International conference on organic agriculture in Scope of environmental problems, Expo - MENOPE: 7th Middle East Natural and Organic Product
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