Journal Article10.1080/02331939008843629
Probabilistische analyse von heuristiken der kombinatorischen optimierung – ein überbllck
1
TL;DR: This work considers the problems Traveling Salesman, Minimum Perfect Matching, Minimum Spanning Tree, Linear Optimization, Bin Packing, Multi-processor-Scheduling, Subset Sum and some problems to random graphs to probabilistic analysis of heuristics.
read more
Abstract: To various problems of combinatorial optimization we consider the question how the value of the optimal solution resp. the values of some approximative solutions are predetermined with high probability to a given distribution. We present results to probabilistic analysis of heuristics. We consider the problems Traveling Salesman, Minimum Perfect Matching. Minimum Spanning Tree, Linear Optimization, Bin Packing, Multi-processor-Scheduling, Subset Sum and some problems to random graphs.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
The parallel complexity of TSP heuristics
G.A.P. Kindervater,A.K. Lenstra +1 more
- 01 Jan 1986
TL;DR: The problems of finding a tour by the nearest neighbor, nearest merger, nearest insertion, cheapest insertion, and farthest insertion heuristics are shown to be P -complete and it is unlikely that such tours can be obtained in polylogarithmic work space on a sequential computer or on a computer with unbounded parallelism.
15
References
•Book
Integer and Combinatorial Optimization
George L. Nemhauser,Laurence A. Wolsey +1 more
- 01 Jan 1988
TL;DR: This chapter discusses the Scope of Integer and Combinatorial Optimization, as well as applications of Special-Purpose Algorithms and Matching.
Integer and Combinatorial Optimization: Nemhauser/Integer and Combinatorial Optimization
George L. Nemhauser,Laurence A. Wolsey +1 more
- 16 Jun 1988
Abstract: FOUNDATIONS. The Scope of Integer and Combinatorial Optimization. Linear Programming. Graphs and Networks. Polyhedral Theory. Computational Complexity. Polynomial-Time Algorithms for Linear Programming. Integer Lattices. GENERAL INTEGER PROGRAMMING. The Theory of Valid Inequalities. Strong Valid Inequalities and Facets for Structured Integer Programs. Duality and Relaxation. General Algorithms. Special-Purpose Algorithms. Applications of Special- Purpose Algorithms. COMBINATORIAL OPTIMIZATION. Integral Polyhedra. Matching. Matroid and Submodular Function Optimization. References. Indexes.
4.4K