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Solving a Truck Dispatching Scheduling Problem Using Branch-and-Cut
Author(s) -
Robert E. Bixby,
Eva K. Lee
Publication year - 1998
Publication title -
operations research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.797
H-Index - 140
eISSN - 1526-5463
pISSN - 0030-364X
DOI - 10.1287/opre.46.3.355
Subject(s) - knapsack problem , solver , heuristics , mathematical optimization , polytope , scheduling (production processes) , integer programming , branch and cut , job shop scheduling , convex hull , computer science , cutting stock problem , mathematics , regular polygon , combinatorics , optimization problem , routing (electronic design automation) , computer network , geometry
A branch-and-cut IP solver is developed for a class of structured 0/1 integer programs arising from a truck dispatching scheduling problem. This problem involves a special class of knapsack equality constraints. Families of facets for the polytopes associated with individual knapsack constraints are identified. In addition, a notion of "conflict graph" is utilized to obtain an approximating node-packing polytope for the convex hull of all 0/1 solutions. The branch-and-cut solver generates cuts based on both the knapsack equality constraints and the approximating node-packing polytope, and incorporates these cuts into a tree-search algorithm that uses problem reformulation and linear programming-based heuristics at each node in the search tree to assist in the solution process. Numerical experiments are performed on large-scale real instances supplied by Texaco Trading & Transportation, Inc. The optimal schedules correspond to cost savings for the company and greater job satisfaction for drivers due to more balanced work schedules and income distribution.

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