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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Computational optimization and applications 3 (1994), S. 7-26 
    ISSN: 1573-2894
    Keywords: network programming ; assignment ; integer programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This manuscript presents a new heuristic algorithm to find near optimal integer solutions for the singly constrained assignment problem. The method is based on Lagrangian duality theory and involves solving a series of pure assignment problems. The software implementation of this heuristic, ASSIGN+1, successfully solved problems having one-half million binary variables (assignment arcs) in less than 17 minutes of wall clock time on a Sequent Symmetry S81 using a single processor. In computational comparisons with MPSX and OSL on an IBM 3081D, the specialized software was from 100 to 1,000 times faster. In computational comparisons with the specialized code of Mazzola and Neebe, we found that ASSIGN+1 was 40 times faster. In computational comparisons with our best alternating path specialized code, we found that ASSIGN+1 was more than three times faster than that code. This new software proved to be very robust as well as fast. The robustness is due to an elaborate scheme used to update the Lagrangean multipliers and the speed is due to the fine code used to solve the pure assignment problems. We also present a modification of the algorithm for the case in which the number of jobs exceeds the number of men along with an empirical analysis of the modified software.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Computational optimization and applications 8 (1997), S. 287-299 
    ISSN: 1573-2894
    Keywords: assignment problem ; integer programming ; Lagrangean relaxation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This manuscript presents a truncated branch-and-bound algorithm toobtain a near optimal solution for the constrained assignment problemin which there are only a few side constraints. At each node of thebranch-and-bound tree a lower bound is obtained by solving a singlyconstrained assignment problem. If needed, Lagrangean relaxationtheory is applied in an attempt to improve this lower bound. Aspecialized branching rule is developed which exploits therequirement that every man be assigned to some job. A softwareimplementation of the algorithm has been tested on problems with fiveside constraints and up to 75,000 binary variables. Solutionsguaranteed to be within 10% of an optimum were obtained for these75,000 variable problems in from two to twenty minutes of CPU time ona Dec Alpha workstation. The behavior of the algorithm for variousproblem characteristics is also studied. This includes the tightnessof the side constraints, the stopping criteria, and the effect whenthe problems are unbalanced having more jobs than men.
    Type of Medium: Electronic Resource
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