190 research outputs found
A Novel Approach to the Common Due-Date Problem on Single and Parallel Machines
This paper presents a novel idea for the general case of the Common Due-Date
(CDD) scheduling problem. The problem is about scheduling a certain number of
jobs on a single or parallel machines where all the jobs possess different
processing times but a common due-date. The objective of the problem is to
minimize the total penalty incurred due to earliness or tardiness of the job
completions. This work presents exact polynomial algorithms for optimizing a
given job sequence for single and identical parallel machines with the run-time
complexities of for both cases, where is the number of jobs.
Besides, we show that our approach for the parallel machine case is also
suitable for non-identical parallel machines. We prove the optimality for the
single machine case and the runtime complexities of both. Henceforth, we extend
our approach to one particular dynamic case of the CDD and conclude the chapter
with our results for the benchmark instances provided in the OR-library.Comment: Book Chapter 22 page
F-theory, GUTs, and the Weak Scale
In this paper we study a deformation of gauge mediated supersymmetry breaking
in a class of local F-theory GUT models where the scale of supersymmetry
breaking determines the value of the mu term. Geometrically correlating these
two scales constrains the soft SUSY breaking parameters of the MSSM. In this
scenario, the hidden SUSY breaking sector involves an anomalous U(1)
Peccei-Quinn symmetry which forbids bare mu and B mu terms. This sector
typically breaks supersymmetry at the desired range of energy scales through a
simple stringy hybrid of a Fayet and Polonyi model. A variant of the
Giudice-Masiero mechanism generates the value mu ~ 10^2 - 10^3 GeV when the
hidden sector scale of supersymmetry breaking is F^(1/2) ~ 10^(8.5) GeV.
Further, the B mu problem is solved due to the mild hierarchy between the GUT
scale and Planck scale. These models relate SUSY breaking with the QCD axion,
and solve the strong CP problem through an axion with decay constant f_a ~
M_(GUT) * mu / L, where L ~ 10^5 GeV is the characteristic scale of gaugino
mass unification in gauge mediated models, and the ratio \mu / L ~
M_(GUT)/M_(pl) ~ 10^(-3). We find f_a ~ 10^12 GeV, which is near the high end
of the phenomenologically viable window. Here, the axino is the goldstino mode
which is eaten by the gravitino. The gravitino is the LSP with a mass of about
10^1 - 10^2 MeV, and a bino-like neutralino is (typically) the NLSP with mass
of about 10^2 - 10^3 GeV. Compatibility with electroweak symmetry breaking also
determines the value of tan(beta) ~ 30 +/- 7.Comment: v3: 94 pages, 9 figures, clarification of Fayet-Polonyi model and
instanton corrections to axion potentia
E6,7,8 Magnetized Extra Dimensional Models
We study 10D super Yang-Mills theory with the gauge groups , and
. We consider the torus/orbifold compacfitication with magnetic fluxes and
Wilson lines. They lead to 4D interesting models with three families of quarks
and leptons, whose profiles in extra dimensions are quasi-localized because of
magnetic fluxes.Comment: 17 pages, 1 figur
A Study of Memetic Search with Multi-parent Combination for UBQP
We present a multi-parent hybrid geneticâtabu algorithm (denoted by GTA) for the Unconstrained Binary Quadratic Programming (UBQP) problem, by incorporating tabu search into the framework of genetic algorithm. In this paper, we propose a new multi-parent combination operator for generating offspring solutions. A pool updating strategy based on a quality-and-distance criterion is used to manage the population. Experimental comparisons with leading methods for the UBQP problem on 25 large public instances demonstrate the efficacy of our proposed algorithm in terms of both solution quality and computational efficiency
An In-Out Approach to Disjunctive Optimization
Abstract. Cutting plane methods are widely used for solving convex optimization problems and are of fundamental importance, e.g., to pro-vide tight bounds for Mixed-Integer Programs (MIPs). This is obtained by embedding a cut-separation module within a search scheme. The importance of a sound search scheme is well known in the Constraint Programming (CP) community. Unfortunately, the âstandard â search scheme typically used for MIP problems, known as the Kelley method, is often quite unsatisfactory because of saturation issues. In this paper we address the so-called Lift-and-Project closure for 0-1 MIPs associated with all disjunctive cuts generated from a given set of elementary disjunction. We focus on the search scheme embedding the generated cuts. In particular, we analyze a general meta-scheme for cutting plane algorithms, called in-out search, that was recently proposed by Ben-Ameur and Neto [1]. Computational results on test instances from the literature are presented, showing that using a more clever meta-scheme on top of a black-box cut generator may lead to a significant improvement
Particle swarm optimization for the Steiner tree in graph and delay-constrained multicast routing problems
This paper presents the first investigation on applying a particle swarm optimization (PSO) algorithm to both the Steiner tree problem and the delay constrained multicast routing problem. Steiner tree problems, being the underlining models of many applications, have received significant research attention within the meta-heuristics community. The literature on the application of meta-heuristics to multicast routing problems is less extensive but includes several promising approaches. Many interesting research issues still remain to be investigated, for example, the inclusion of different constraints, such as delay bounds, when finding multicast trees with minimum cost. In this paper, we develop a novel PSO algorithm based on the jumping PSO (JPSO) algorithm recently developed by Moreno-Perez et al. (Proc. of the 7th Metaheuristics International Conference, 2007), and also propose two novel local search heuristics within our JPSO framework. A path replacement operator has been used in particle moves to improve the positions of the particle with regard to the structure of the tree. We test the performance of our JPSO algorithm, and the effect of the integrated local search heuristics by an extensive set of experiments on multicast routing benchmark problems and Steiner tree problems from the OR library. The experimental results show the superior performance of the proposed JPSO algorithm over a number of other state-of-the-art approaches
Prospect theory-based portfolio optimisation: An empirical study and analysis using intelligent algorithms
The first author was part funded by RFBR (grant 14-01-00140)
Uniformization of frontiers in non-radial ZSG-DEA models: an application to airport revenues
Population Heuristics
Standard heuristics in Operations Research (such as greedy, tabu search and simulated annealing) work on improving a single current solution. Population heuristics use a number of current solutions and combine them together to generate new solutions. Heuristic algorithms encountered in the literature that can generically be classified as population heuristics include genetic algorithms, hybrid genetic algorithms, memetic algorithms, scatter search algorithms and bionomic algorithms. In this tutorial paper we discuss the basic features of population heuristics and provide practical advice as to their effective use for solving Operations Research problems. 1 1. INTRODUCTION In Operations Research (OR), over the years, a number of standard heuristic algorithms have appeared. In the early years of OR heuristics were especially tailored to the problem under consideration. As OR advanced a number of basic heuristic ideas began to be formalised. These included ideas such as greedy (seek th..
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