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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 4 (1995), S. 347-374 
    ISSN: 1573-2894
    Keywords: mathematical programming ; assignment ; networks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This manuscript presents a specialized primal simplex algorithm to obtain near optimal integer solutions for the singly constrained assignment problem. An optimal solution for the continuous relaxation of the problem is obtained by generalizing the alternating basis algorithm of Barr, Glover, and Klingman for the pure assignment problem. Near optimal integer solutions are obtained by pivoting into the optimal basis the slack variable associated with the side constraint. Our empirical analysis indicated that for our test problems the soft-ware implementation of this algorithm was six times faster than CPLEX and four times faster than NETSIDE (a specialized code for network problems with side constraints). The integer solutions obtained in our tests were typically within 2% of the optimum of the continuous relaxation.
    Type of Medium: Electronic Resource
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