Global supply chains of high value low volume products

Imperial Users onl

A Sustainable Supply Chain Model of Relationship Between Wood Supplier and Furniture Industry in Indonesia

Wooden furniture industry is an important industry sector in Indonesia, because many people\u27s welfare relyon this industry sector and the industry has a big social and environmental impacts. Many wooden furnitureindustries in Indonesia, especially in Central Java Province face problems related to the sustainability. The relationbetween wood suppliers and furniture industry is studied in this paper. A sustainable supply chain management (s-SCM) model is proposed as an approach for solutions for the problems. The approach is chosen due to the characteristics of the problems that related to economic, social, and environmental problems. This aim of this paper is to determine how much supply teak wood must be provided by PP to satisfy furniture industry demand, how much production capacity that must be increased and how large forest area that must be planted in order to achieve environmental and social goals without sacrificing economical goals much. Goal programming (GP) is chosen for solving the problems, because the goals are to maximize the total benefit,minimize the total loss and anticipate the conflicts between goals. Numerical trial based on observation in teak wooden furniture industry in Central Java was used to illustrate our findings. Using pareto efficient principle, the model can satisfy all goals that need to be achieved. Numerical results can be used by decision makers in teak wood industry to analyze the trade-off among several set of alternative solutions

Approximations of countably-infinite linear programs over bounded measure spaces

We study a class of countably-infinite-dimensional linear programs (CILPs) whose feasible sets are bounded subsets of appropriately defined weighted spaces of measures. We show how to approximate the optimal value, optimal points, and minimal points of these CILPs by solving finite-dimensional linear programs. The errors of our approximations converge to zero as the size of the finite-dimensional program approaches that of the original problem and are easy to bound in practice. We discuss the use of our methods in the computation of the stationary distributions, occupation measures, and exit distributions of Markov~chains

Solving Factored MDPs with Hybrid State and Action Variables

Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automated decision support systems. In this paper, we describe a novel hybrid factored Markov decision process (MDP) model that allows for a compact representation of these problems, and a new hybrid approximate linear programming (HALP) framework that permits their efficient solutions. The central idea of HALP is to approximate the optimal value function by a linear combination of basis functions and optimize its weights by linear programming. We analyze both theoretical and computational aspects of this approach, and demonstrate its scale-up potential on several hybrid optimization problems