Journal ArticleDOI
Exact solution of crew scheduling problems using the set partitioning model: Recent successful applications
Roy E. Marsten,Fred Shepardson +1 more
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This paper focuses on recent developments that have made this model more attractive and have resulted in several successful implementations, as well as new solution techniques employing Lagrangian relaxation and subgradient optimization.Abstract:
The set partitioning model of the crew rotation problem has been well known for many years. This paper focuses on recent developments that have made this model more attractive and have resulted in several successful implementations. These developments include improved problem conceptualizations and decompositions, as well as new solution techniques employing Lagrangian relaxation and subgradient optimization. Experience is reported from The Flying Tiger Line, Pacific Southwest Airways, Continental Airlines, and Helsinki City Transport. A case is made for work on heuristic decomposition methods to break large problems into moderate sized pieces that can be solved exactly.read more
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Journal ArticleDOI
A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems
Brian P. Gerkey,Maja J. Matarić +1 more
TL;DR: A domain-independent taxonomy of MRTA problems is given, and it is shown how many such problems can be viewed as instances of other, well-studied, optimization problems.
Journal ArticleDOI
Solving airline crew scheduling problems by branch-and-cut
Karla Hoffman,Manfred Padberg +1 more
TL;DR: The branch-and-cut solver as discussed by the authors generates cutting planes based on the underlying structure of the polytope defined by the convex hull of the feasible integer points and incorporates these cuts into a tree-search algorithm that uses automatic reformulation procedures, heuristics and linear programming technology to assist in the solution.
Journal ArticleDOI
An Annotated Bibliography of Personnel Scheduling and Rostering
TL;DR: This annotated bibliography puts together a comprehensive collection of some 700 references in this area, focusing mainly on algorithms for generating rosters and personnel schedules but also covering related areas such as workforce planning and estimating staffing requirements.
Book ChapterDOI
Stochastic and dynamic networks and routing
TL;DR: In this paper, the authors present a general framework for formulating and solving stochastic, dynamic network problems, including shortest paths, traveling salesman-type problems and vehicle routing.
References
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Journal ArticleDOI
Validation of subgradient optimization
TL;DR: It is concluded that the “relaxation” procedure for approximately solving a large linear programming problem related to the traveling-salesman problem shows promise for large-scale linear programming.
Journal ArticleDOI
The traveling-salesman problem and minimum spanning trees: Part II
Michael Held,Richard M. Karp +1 more
TL;DR: An efficient iterative method for approximating this bound closely from below is presented, and a branch-and-bound procedure based upon these considerations has easily produced proven optimum solutions to all traveling-salesman problems presented to it.
Journal ArticleDOI
The Set-Partitioning Problem: Set Covering with Equality Constraints
TL;DR: This paper gives an enumerative algorithm for the set-partitioning problem, that is, theset-covering problem with equality constraints, and presents computational results for real and randomly generated problems.
Journal ArticleDOI
The Airline Crew Scheduling Problem: A Survey
TL;DR: A survey of the different approaches studied by a number of airlines in the past few years to attempt to optimize the allocation of crews to flights can be found in this article, where the authors cover the generation, costing, reduction, and optimization of such matrices.
Journal ArticleDOI
Set Covering by Single-Branch Enumeration with Linear-Programming Subproblems
TL;DR: The algorithm has been found to be highly effective for a good number of relatively large problems and stems from an efficient suboptimization procedure, which constructs excellent integer solutions from the solutions to linear-programming subproblems.
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