Higher-level RLT or disjunctive cuts based on a partial enumeration strategy for 0-1 mixed-integer programs

In this paper, we consider the generation of disjunctive cuts for 0-1 mixed-integer programs by conducting a partial exploration of the branch-and-bound tree using quick Lagrangian primal and dual updates. We analyze alternative cut generation strategies based on formulating different disjunctions and adopting various choices of normalization techniques, and indicate how these inequalities can also be generated using a projection from a related high-order lifted formulation obtained via the Reformulation-Linearization Technique of Sherali and Adams. We conclude by presenting a brief computational study that motivates the potential benefits of this procedure.

[1]  Yurii Nesterov,et al.  Smooth minimization of non-smooth functions , 2005, Math. Program..

[2]  Hanif D. Sherali,et al.  Recovery of primal solutions when using subgradient optimization methods to solve Lagrangian duals of linear programs , 1996, Oper. Res. Lett..

[3]  Michael Patriksson,et al.  Ergodic, primal convergence in dual subgradient schemes for convex programming , 1999, Mathematical programming.

[4]  Hanif D. Sherali,et al.  A variable target value method for nondifferentiable optimization , 2000, Oper. Res. Lett..

[5]  Egon Balas,et al.  programming: Properties of the convex hull of feasible points * , 1998 .

[6]  Hanif D. Sherali,et al.  On embedding the volume algorithm in a variable target value method , 2004, Oper. Res. Lett..

[7]  Krzysztof C. Kiwiel,et al.  Proximity control in bundle methods for convex nondifferentiable minimization , 1990, Math. Program..

[8]  H. Sherali,et al.  A primal-dual conjugate subgradient algorithm for specially structured linear and convex programming problems , 1989 .

[9]  Francisco Barahona,et al.  The volume algorithm: producing primal solutions with a subgradient method , 2000, Math. Program..

[10]  Marshall L. Fisher,et al.  The Lagrangian Relaxation Method for Solving Integer Programming Problems , 2004, Manag. Sci..

[11]  Hanif D. Sherali,et al.  Enhancing Lagrangian Dual Optimization for Linear Programs by Obviating Nondifferentiability , 2007, INFORMS J. Comput..

[12]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[13]  David Applegate,et al.  Finding Cuts in the TSP (A preliminary report) , 1995 .

[14]  Warren P. Adams,et al.  A hierarchy of relaxation between the continuous and convex hull representations , 1990 .

[15]  Egon Balas Disjunctive Programming , 2010, 50 Years of Integer Programming.

[16]  Hanif D. Sherali,et al.  A Hierarchy of Relaxations Between the Continuous and Convex Hull Representations for Zero-One Programming Problems , 1990, SIAM J. Discret. Math..

[17]  Boris Polyak Minimization of unsmooth functionals , 1969 .

[18]  Hanif D. Sherali,et al.  On the generation of deep disjunctive cutting planes , 1980 .

[19]  P. Camerini,et al.  On improving relaxation methods by modified gradient techniques , 1975 .

[20]  Egon Balas,et al.  Generating lift-and-project cuts from the LP simplex tableau: open source implementation and testing of new variants , 2009, Math. Program. Comput..

[21]  Hanif D. Sherali,et al.  Optimization with disjunctive constraints , 1980 .

[22]  Naum Zuselevich Shor,et al.  Minimization Methods for Non-Differentiable Functions , 1985, Springer Series in Computational Mathematics.

[23]  J. Shapiro A Survey of Lagrangian Techniques for Discrete Optimization. , 1979 .

[24]  Philip Wolfe,et al.  Validation of subgradient optimization , 1974, Math. Program..

[25]  Warren P. Adams,et al.  A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems , 1998 .

[26]  Hanif D. Sherali,et al.  A Hierarchy of Relaxations and Convex Hull Characterizations for Mixed-integer Zero-one Programming Problems , 1994, Discret. Appl. Math..