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Management Studies (Department)

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Author: search.filters.author.Lamb, John Douglas

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Now showing 1 - 4 of 4
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    Making Cornish–Fisher Distributions Fit
    (2016) Lamb, John Douglas; Monville, M.E.; Tee, Kai-Hong; University of Aberdeen.Business Management; University of Aberdeen.Energy
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    Data Envelopment Analysis Models of Investment Funds
    (University of Aberdeen: Business School, 2010) Lamb, John Douglas; Tee, Kai-Hong; University of Aberdeen.Business Management
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    The Subtour Centre Problem
    (2007-03-20T15:09:05Z) Lamb, John Douglas; University of Aberdeen, Business School, Management Studies
    The subtour centre problem is the problem of finding a closed trail S of bounded length on a connected simple graph G that minimises the maximum distance from S to any vertex ofG. It is a central location problem related to the cycle centre and cycle median problems (Foulds et al., 2004; Labbé et al., 2005) and the covering tour problem (Current and Schilling, 1989). Two related heuristics and an integer linear programme are formulated for it. These are compared numerically using a range of problems derived from tsplib (Reinelt, 1995). The heuristics usually perform substantially better then the integer linear programme and there is some evidence that the simpler heuristics perform better on the less dense graphs that may be more typical of applications.
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    Insertion Heuristics for Central Cycle Problems
    (2006) Lamb, John Douglas; University of Aberdeen, Business School, Management Studies
    A central cycle problem requires a cycle that is reasonably short and keeps a the maximum distance from any node not on the cycle to its nearest node on the cycle reasonably low. The objective may be to minimise maximumdistance or cycle length and the solution may have further constraints. Most classes of central cycle problems are NP-hard. This paper investigates insertion heuristics for central cycle problems, drawing on insertion heuristics for p-centres [7] and travelling salesman tours [21]. It shows that a modified farthest insertion heuristic has reasonable worstcase bounds for a particular class of problem. It then compares the performance of two farthest insertion heuristics against each other and against bounds (where available) obtained by integer programming on a range of problems from TSPLIB [20]. It shows that a simple farthest insertion heuristic is fast, performs well in practice and so is likely to be useful for a general problems or as the basis for more complex heuristics for specific problems.