Binary artificial algae algorithm for multidimensional knapsack problems

The multidimensional knapsack problem (MKP) is a well-known NP-hard optimization problem. Various meta-heuristic methods are dedicated to solve this problem in literature. Recently a new meta-heuristic algorithm, called artificial algae algorithm (AAA), was presented, which has been successfully applied to solve various continuous optimization problems. However, due to its continuous nature, AAA cannot settle the discrete problem straightforwardly such as MKP. In view of this, this paper proposes a binary artificial algae algorithm (BAAA) to efficiently solve MKP. This algorithm is composed of discrete process, repair operators and elite local search. In discrete process, two logistic functions with different coefficients of curve are studied to achieve good discrete process results. Repair operators are performed to make the solution feasible and increase the efficiency. Finally, elite local search is introduced to improve the quality of solutions. To demonstrate the efficiency of our proposed algorithm, simulations and evaluations are carried out with total of 94 benchmark problems and compared with other bio-inspired state-of-the-art algorithms in the recent years including MBPSO, BPSOTVAC, CBPSOTVAC, GADS, bAFSA, and IbAFSA. The results show the superiority of BAAA to many compared existing algorithms

A constraint-based framework to model harmony for algorithmic composition

Music constraint systems provide a rule-based approach to composition. Existing systems allow users to constrain the harmony, but the constrainable harmonic information is restricted to pitches and intervals between pitches. More abstract analytical information such as chord or scale types, their root, scale degrees, enharmonic note representations, whether a note is the third or fifth of a chord and so forth are not supported. However, such information is important for modelling various music theories. This research proposes a framework for modelling harmony at a high level of abstraction. It explicitly represents various analytical information to allow for complex theories of harmony. It is designed for efficient propagation-based constraint solvers. The framework supports the common 12-tone equal temperament, and arbitrary other equal temperaments. Users develop harmony models by applying user-defined constraints to its music representation. Three examples demonstrate the expressive power of the framework: (1) an automatic melody harmonisation with a simple harmony model; (2) a more complex model implementing large parts of Schoenberg’s tonal theory of harmony; and (3) a composition in extended tonality. Schoenberg’s comprehensive theory of harmony has not been computationally modelled before, neither with constraints programming nor in any other way.

Reserve Capacity Model for Optimizing Traffic Signal Timings with an Equity Constraint

This paper represents a solution algorithm for optimizing traffic signal timings in urban road networks by considering reserve capacity with an equity constraint. It is well known that the variation of signal timings in a road network may cause an inequity issue with regard to the travel costs of road users travelling between origin-destination (O-D) pairs. That is, the users may be influenced differently by changing traffic signal timings. In this context, the bilevel programming model is proposed for finding reserve capacity for signalized road networks by taking into account the equity issue. In the upper level, the reserve capacity is maximized with an equity constraint, whereas deterministic user equilibrium problem is dealt in the lower level. In order to solve the proposed model, a heuristic solution algorithm based on harmony search combined with a penalty function approach is developed. The application of the proposed model is illustrated for an example road network taken from a literature

Gravitational Search and Harmony Search Algorithms for Solving the Chemical Kinetics Optimization Problems

The article is dedicated to the analysis of the global optimization algorithms application to the solution of inverse problems of chemical kinetics. Two heuristic algorithms are considered - the gravitational search algorithm and the harmony algorithm. The article describes the algorithms, as well as the application of these algorithms to the optimization of test functions. After that, these algorithms are used to search for the kinetic parameters of two chemical processes – propane pre-reforming on Ni-catalyst and catalytic isomerization of pentane-hexane fraction. For the first process both algorithms showed approximately the same solution, while for the second problem the gravitational search algorithm showed a smaller value of the minimizing function. Wherefore, it is concluded that on large-scale problems it is better to use the gravitational search algorithm rather than the harmony algorithm, while obtaining a smaller value of the minimizing function in a minimum time. On low-scale problems both algorithms showed approximately the same result, while demonstrating the coincidence of the calculated data with the experimental ones

Preventive maintenance effect on the aggregate production planning model with tow-phase production systems: modeling and solution methods

This paper develops two mixed integer linear programming (MILP) models for an integrated aggregate production planning (APP) system with return products, breakdowns and preventive maintenance (PM). The goal is to minimize the cost of production with regard to PM costs, breakdowns, the number of laborers and inventory levels and downtimes. Due to NP-hard class of APP, we implement a harmony search (HS) algorithm and vibration damping optimization (VDO) algorithm for solving these models. Next, the Taguchi method is conducted to calibrate the parameter of the metaheuristics and select the optimal levels of factors influencing the algorithm’s performance. Computational results tested on a set of randomly generated instances show the efficiency of the vibration damping optimization algorithm against the harmony search algorithm. We find VDO algorithm to obtain best quality solutions for APP with breakdowns and PM, which could be efficient for large scale problems. Finally, the computational results show that the objective function values obtained by APP with PM are better than APP with breakdown results

Optimal Placement Algorithms for Virtual Machines

Cloud computing provides a computing platform for the users to meet their demands in an efficient, cost-effective way. Virtualization technologies are used in the clouds to aid the efficient usage of hardware. Virtual machines (VMs) are utilized to satisfy the user needs and are placed on physical machines (PMs) of the cloud for effective usage of hardware resources and electricity in the cloud. Optimizing the number of PMs used helps in cutting down the power consumption by a substantial amount. In this paper, we present an optimal technique to map virtual machines to physical machines (nodes) such that the number of required nodes is minimized. We provide two approaches based on linear programming and quadratic programming techniques that significantly improve over the existing theoretical bounds and efficiently solve the problem of virtual machine (VM) placement in data centers

Topology and Shape Optimization of Hydrodynamically–Lubricated Bearings for Enhanced Load-Carrying Capacity

Bearings are basic and essential components of nearly all machinery. They must be designed to work under different loads, speeds, and environments. Of all the performance parameters, load-carrying capacity (LCC) is often the most crucial design constraint. The objective of this research is to investigate different design methodologies that significantly improve the LCC of liquid-lubricated bearings. This goal can be achieved by either altering the surface texture or the bearing geometrical configuration. The methodology used here is based on mathematical topological/shape optimization algorithms. These methods can effectively improve the design performance while avoiding time-consuming trial-and-error design techniques. The first category of design studied is a micro-scale mechanical self-adaptive type which can provide “flexible surface texturing”. An accurate 3D model based on the classic plate theory and thin film lubrication is developed and a shape optimization analysis is carried out. Special attention is given to the cavitation phenomena and its numerical analysis. Also proposed is a numerical procedure to improve the convergence rate and stability of the Elrod cavitation algorithm. The idea of using self-adaptive mechanism to improve LCC is also adopted for thrust bearings. Novel flexible-pad thrust bearing designs that provide an optimum load-responsive mechanism are presented and an accurate multi-physics model that considers the coupled mechanism between the lubricant pressure and the pad deformation is developed. The optimum shapes for different bearing geometries are given and a detailed design guideline is provided for optimum performance. The second category of design studied focuses on bearing geometrical configuration. The optimum shape of finite width sectorial sliders, which is an open problem in the field, is determined for the first time in this research using topological optimization algorithms. Also three suboptimum solutions for special cases of 2D step profile, constant film thickness in the radial direction and constant film depth with quadrilateral shape are presented. These configurations are particularly attractive because they can be easily manufactured. The optimum shape of bearings with periodic surface grooves is also determined in this research. It is shown that the optimum shape is dependent to the aspect ratio of the grooves and it can change from elongated “heart-like” shapes to spiral-like shapes. A series of laboratory tests to authenticate the theoretical development is carried out. Results show very good agreement with the theory validating the accuracy of the model. Finally, the optimum geometry of spiral grooves that provide the highest LCC in liquid-lubricated parallel flat surface bearings is determined and a detailed design guideline is provided. The thermal effects are also considered and an approximate thermo-hydrodynamic model is developed for a range of seal geometries and operating conditions

Block matching algorithm based on Harmony Search optimization for motion estimation

Motion estimation is one of the major problems in developing video coding applications. Among all motion estimation approaches, Block-matching (BM) algorithms are the most popular methods due to their effectiveness and simplicity for both software and hardware implementations. A BM approach assumes that the movement of pixels within a defined region of the current frame can be modeled as a translation of pixels contained in the previous frame. In this procedure, the motion vector is obtained by minimizing a certain matching metric that is produced for the current frame over a determined search window from the previous frame. Unfortunately, the evaluation of such matching measurement is computationally expensive and represents the most consuming operation in the BM process. Therefore, BM motion estimation can be viewed as an optimization problem whose goal is to find the best-matching block within a search space. The simplest available BM method is the Full Search Algorithm (FSA) which finds the most accurate motion vector through an exhaustive computation of all the elements of the search space. Recently, several fast BM algorithms have been proposed to reduce the search positions by calculating only a fixed subset of motion vectors despite lowering its accuracy. On the other hand, the Harmony Search (HS) algorithm is a population-based optimization method that is inspired by the music improvisation process in which a musician searches for harmony and continues to polish the pitches to obtain a better harmony. In this paper, a new BM algorithm that combines HS with a fitness approximation model is proposed. The approach uses motion vectors belonging to the search window as potential solutions. A fitness function evaluates the matching quality of each motion vector candidate.Comment: 25 Pages. arXiv admin note: substantial text overlap with arXiv:1405.472