The bounded interval generalized assignment model

The bounded interval generalized assignment model is a “many-for-one” assignment model. Each task must be assigned to exactly one agent; however, each agent can be assigned multiple tasks as long as the agent resource consumed by performing the assigned tasks falls within a specified interval. The bounded interval generalized assignment model is formulated, and an algorithm for its solution is developed. Algorithms for the bounded interval versions of the semiassignment model and sources-to-uses transportation model are also discussed.     

Implicit enumeration based algorithms for postoptimizing zero-one programs

It has been shown by G. Roodman that useful postoptimization capabilities for the 0-1 integer programming problem can be obtained from an implicit enumeration algorithm modified to classify and collect all fathomed partial solutions. This paper extends the the approach as follows: 1) Improved parameter ranging formulas are obtained by higher resolution classification criteria. 2) Parameters may be changed so as to tighten the original problem, in addition to relaxing it. 3) An efficient storage structure is presented to cope with difficult data collection task implicit in this approach. 4) Finally, computer implementation is facilitated by the elaboration of a unified set of algorithms.     

Intersection cuts from outer polars of truncated cubes

A truncated cube, by which we mean the convex hull of a subset of the vertices of the unit cube, has an outer polar whose facets are a subset of the facets of the octahedron (the outer polar of the cube). We discuss procedures for generating valid truncations of the cube from the problem constraints, in the case of 0-1 integer programs, and for intersecting the halflines defined by the constraints that are tight for a basic solution to the linear program, with successive facets of the outer polars of these truncated cubes. The cutting planes obtained in this way are compared to other cuts.