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ABSTRACTThis paper describes a goal programming procedure for determining satisfactory output plans for a work center. The situation being modeled is one in which work center inputs are known but vary significantly across time periods. Input levels are fixed relative to a given master production schedule, and output levels can be varied only within certain prescribed limits, at least in the short term. The similarity of the output planning problem to the more familiar aggregate planning problem is noted and discussed.

AbstractThe pure fixed charge transportation problem (PFCTP) is a variation of the fixed charge transportation problem (FCTP) in which there are only fixed costs to be incurred when a route is opened. We present in this paper a direct search procedure using the LIFO decision rule for branching. This procedure is enhanced by the use of 0–1 knapsack problems which determine bounds on partial solutions. Computational results are presented and discussed.

AbstractThe loading problem involves the optimal allocation of n objects, each having a specified weight and value, to m boxes, each of specified capacity. While special cases of these problems can be solved with relative ease, the general problem having variable item weights and box sizes can become very difficult to solve. This paper presents a heuristic procedure for solving large loading problems of the more general type. The procedure uses a surrogate procedure for reducing the original problem to a simpler knapsack problem, the solution of which is then employed in searching for feasible solutions to the original problem. The procedure is easy to apply, and is capable of identifying optimal solutions if they are found.

AbstractThe 0‐1 multiple‐knapsack problem is an extension of the well‐known 0‐1 knapsack problem. It is a problem of assigning m objects, each having a value and a weight, to n knapsacks in such a way that the total weight in each knapsack is less than its capacity limit and the total value in the knapsacks is maximized.A branch‐and‐bound algorithm for solving the problem is developed and tested. Branching rules that avoid the search of redundant partial solutions are used in the algorithm. Various bounding techniques, including Lagrangean and surrogate relaxations, are investigated and compared.

Chapter 2 (Stoian et al.) draws attention to the link between VCD and smallholder livelihood strategies that comprise a complex mix of subsistence and market-oriented activities and that are diversified to meet multiple livelihood goals and mitigate risks; and the authors address the related implications for the design and assessment of value-chain interventions. They question some of the underlying assumptions of NGOs, government agencies, and private-sector agents seeking to link smallholders to higher-value markets ; PR ; IFPRI1; CRP2; C Improving markets and trade ; MTID; PIM ; CGIAR Research Program on Policies, Institutions, and Markets (PIM)

"HJ 2005 U.S." ; "January 18, 1979." ; Includes bibliographical references. ; Mode of access: Internet. ; Cover title.