30 research outputs found
Genetic Algorithm for Combinatorial Path Planning: The Subtour Problem
The purpose of this paper is to present a combinatorial planner for autonomous systems. The approach is demonstrated
on the so-called subtour problem, a variant of the classical traveling salesman problem (TSP): given a set of possible goals/targets, the optimal strategy is sought that connects ≤ goals. The proposed solution method is a Genetic Algorithm coupled with a heuristic local search. To validate the approach, the method has been benchmarked against TSPs and subtour problems with known optimal solutions. Numerical experiments demonstrate the success
of the approach
Transgenic approaches for improving fungal disease resistance in groundnut
Fungal diseases in groundnut are the most significant limiting factor causing more than 50%
yield losses throughout the world. Genetic enhancement in groundnut through conventional breeding
and chemical control has yielded only limited success. More recently, genetic transformation has led
to possibility of transforming crops for increased resistance to fungal diseases. This review summarizes
the advances of genetic engineering applied for improvement of groundnut disease resistance against
fungal pathogens. Fungal resistant transgene of plant, bacterial or fungal origin can be introduced into
groundnut for enhanced disease resistance. Progress in engineering fungal disease resistance in
transgenic ground nut has been accomplished through expression of PR proteins, antifungal proteins,
antimicrobial proteins, ribosome-inactivating proteins (RIP) and phytoalexins
The Optimum Communication Spanning Tree Problem : properties, models and algorithms
For a given cost matrix and a given communication requirement matrix, the OCSTP is defined as finding a spanning tree that minimizes the operational cost of the network. OCST can be used to design of more efficient communication and transportation networks, but appear also, as a subproblem, in hub location and sequence alignment problems.
This thesis studies several mixed integer linear optimization formulations of the OCSTP and proposes a new one. Then, an efficient Branch & Cut algorithm derived from the Benders decomposition of one of such formulations is used to successfully solve medium-sized instances of the OCSTP.
Additionally, two new combinatorial lower bounds, two new heuristic algorithms and a new family of spanning tree neighborhoods based on the Dandelion Code are presented and tested.Postprint (published version
From Parameter Tuning to Dynamic Heuristic Selection
The importance of balance between exploration and exploitation plays a crucial role while solving combinatorial optimization problems. This balance is reached by two general techniques: by using an appropriate problem solver and by setting its proper parameters. Both problems were widely studied in the past and the research process continues up until now. The latest studies in the field of automated machine learning propose merging both problems, solving them at design time, and later strengthening the results at runtime. To the best of our knowledge, the generalized approach for solving the parameter setting problem in heuristic solvers has not yet been proposed. Therefore, the concept of merging heuristic selection and parameter control have not been introduced.
In this thesis, we propose an approach for generic parameter control in meta-heuristics by means of reinforcement learning (RL). Making a step further, we suggest a technique for merging the heuristic selection and parameter control problems and solving them at runtime using RL-based hyper-heuristic. The evaluation of the proposed parameter control technique on a symmetric traveling salesman problem (TSP) revealed its applicability by reaching the performance of tuned in online and used in isolation underlying meta-heuristic. Our approach provides the results on par with the best underlying heuristics with tuned parameters.:1 Introduction 1
1.1 Motivation 1
1.2 Research objective 2
1.3 Solution overview 2
2 Background and RelatedWork Analysis 3
2.1 Optimization Problems and their Solvers 3
2.2 Heuristic Solvers for Optimization Problems 9
2.3 Setting Algorithm Parameters 19
2.4 Combined Algorithm Selection and Hyper-Parameter Tuning Problem 27
2.5 Conclusion on Background and Related Work Analysis 28
3 Online Selection Hyper-Heuristic with Generic Parameter Control 31
3.1 Combined Parameter Control and Algorithm Selection Problem 31
3.2 Search Space Structure 32
3.3 Parameter Prediction Process 34
3.4 Low-Level Heuristics 35
3.5 Conclusion of Concept 36
4 Implementation Details 37
4.2 Search Space 40
4.3 Prediction Process 43
4.4 Low Level Heuristics 48
4.5 Conclusion 52
5 Evaluation 55
5.1 Optimization Problem 55
5.2 Environment Setup 56
5.3 Meta-heuristics Tuning 56
5.4 Concept Evaluation 60
5.5 Analysis of HH-PC Settings 74
5.6 Conclusion 79
6 Conclusion 81
7 FutureWork 83
7.1 Prediction Process 83
7.2 Search Space 84
7.3 Evaluations and Benchmarks 84
Bibliography 87
A Evaluation Results 99
A.1 Results in Figures 99
A.2 Results in numbers 10
A branch, price, and cut approach to solving the maximum weighted independent set problem
The maximum weight-independent set problem (MWISP) is one of the most
well-known and well-studied NP-hard problems in the field of combinatorial
optimization.
In the first part of the dissertation, I explore efficient branch-and-price (B&P)
approaches to solve MWISP exactly. B&P is a useful integer-programming tool for
solving NP-hard optimization problems. Specifically, I look at vertex- and edge-disjoint
decompositions of the underlying graph. MWISPâÂÂs on the resulting subgraphs are less
challenging, on average, to solve. I use the B&P framework to solve MWISP on the
original graph G using these specially constructed subproblems to generate columns. I
demonstrate that vertex-disjoint partitioning scheme gives an effective approach for
relatively sparse graphs. I also show that the edge-disjoint approach is less effective than
the vertex-disjoint scheme because the associated DWD reformulation of the latter
entails a slow rate of convergence.
In the second part of the dissertation, I address convergence properties associated
with Dantzig-Wolfe Decomposition (DWD). I discuss prevalent methods for improving the rate of convergence of DWD. I also implement specific methods in application to the
edge-disjoint B&P scheme and show that these methods improve the rate of
convergence.
In the third part of the dissertation, I focus on identifying new cut-generation
methods within the B&P framework. Such methods have not been explored in the
literature. I present two new methodologies for generating generic cutting planes within
the B&P framework. These techniques are not limited to MWISP and can be used in
general applications of B&P. The first methodology generates cuts by identifying faces
(facets) of subproblem polytopes and lifting associated inequalities; the second
methodology computes Lift-and-Project (L&P) cuts within B&P. I successfully
demonstrate the feasibility of both approaches and present preliminary computational
tests of each
A Polyhedral Study of Mixed 0-1 Set
We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set
The Borexino detector at the Laboratori Nazionali del Gran Sasso
Borexino, a large volume detector for low energy neutrino spectroscopy, is
currently running underground at the Laboratori Nazionali del Gran Sasso,
Italy. The main goal of the experiment is the real-time measurement of sub MeV
solar neutrinos, and particularly of the mono energetic (862 keV) Be7 electron
capture neutrinos, via neutrino-electron scattering in an ultra-pure liquid
scintillator. This paper is mostly devoted to the description of the detector
structure, the photomultipliers, the electronics, and the trigger and
calibration systems. The real performance of the detector, which always meets,
and sometimes exceeds, design expectations, is also shown. Some important
aspects of the Borexino project, i.e. the fluid handling plants, the
purification techniques and the filling procedures, are not covered in this
paper and are, or will be, published elsewhere (see Introduction and
Bibliography).Comment: 37 pages, 43 figures, to be submitted to NI