Mathematical Programming, ISSN 0025-5610, 2/2013, Volume 137, Issue 1, pp. 91 - 129

...–backward splitting algorithm, the gradient projection and some proximal regularization of the Gauss–Seidel method in a nonconvex setting. Our results are illustrated through feasibility problems, or iterative thresholding procedures for compressive sensing.

Tame optimization | 65K15 | Theoretical, Mathematical and Computational Physics | Alternating minimization | Mathematics | Forward–backward splitting | Descent methods | 90C53 | Mathematical Methods in Physics | Iterative thresholding | Calculus of Variations and Optimal Control; Optimization | Proximal algorithms | Sufficient decrease | Combinatorics | 47J25 | Kurdyka–Łojasiewicz inequality | o-minimal structures | Nonconvex nonsmooth optimization | 34G25 | Semi-algebraic optimization | 47J30 | Mathematics of Computing | 90C25 | Numerical Analysis | Block-coordinate methods | Relative error | 49M15 | 49M37 | 47J35 | Kurdyka-Łojasiewicz inequality | Forward-backward splitting | MATHEMATICS, APPLIED | Kurdyka-Lojasiewicz inequality | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | POINT ALGORITHM | Methods | Algorithms | Studies | Algebra | Analysis | Data smoothing | Optimization | Mathematical programming | Splitting | Gauss-Seidel method | Mathematical analysis | Minimization | Descent | Convergence

Tame optimization | 65K15 | Theoretical, Mathematical and Computational Physics | Alternating minimization | Mathematics | Forward–backward splitting | Descent methods | 90C53 | Mathematical Methods in Physics | Iterative thresholding | Calculus of Variations and Optimal Control; Optimization | Proximal algorithms | Sufficient decrease | Combinatorics | 47J25 | Kurdyka–Łojasiewicz inequality | o-minimal structures | Nonconvex nonsmooth optimization | 34G25 | Semi-algebraic optimization | 47J30 | Mathematics of Computing | 90C25 | Numerical Analysis | Block-coordinate methods | Relative error | 49M15 | 49M37 | 47J35 | Kurdyka-Łojasiewicz inequality | Forward-backward splitting | MATHEMATICS, APPLIED | Kurdyka-Lojasiewicz inequality | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | POINT ALGORITHM | Methods | Algorithms | Studies | Algebra | Analysis | Data smoothing | Optimization | Mathematical programming | Splitting | Gauss-Seidel method | Mathematical analysis | Minimization | Descent | Convergence

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 7/2014, Volume 162, Issue 1, pp. 107 - 132

...–Backward algorithm. However, the latter algorithm may suffer from slow convergence. We propose an acceleration strategy based on the use of variable metrics and of the Majorize–Minimize principle...

Forward–Backward algorithm | Nonconvex optimization | Proximity operator | Mathematics | Theory of Computation | Optimization | Image reconstruction | Majorize–Minimize algorithms | Calculus of Variations and Optimal Control; Optimization | Operations Research/Decision Theory | Nonsmooth optimization | Applications of Mathematics | Engineering, general | Forward-Backward algorithm | Majorize-Minimize algorithms | SIGNAL | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | NOISE | OPTIMIZATION | Algorithms | Studies | Optimization algorithms | Analysis | Image processing systems | Mathematical analysis | Texts | Strategy | Mathematical models | Convergence | Engineering Sciences | Computer Science | Signal and Image processing

Forward–Backward algorithm | Nonconvex optimization | Proximity operator | Mathematics | Theory of Computation | Optimization | Image reconstruction | Majorize–Minimize algorithms | Calculus of Variations and Optimal Control; Optimization | Operations Research/Decision Theory | Nonsmooth optimization | Applications of Mathematics | Engineering, general | Forward-Backward algorithm | Majorize-Minimize algorithms | SIGNAL | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | NOISE | OPTIMIZATION | Algorithms | Studies | Optimization algorithms | Analysis | Image processing systems | Mathematical analysis | Texts | Strategy | Mathematical models | Convergence | Engineering Sciences | Computer Science | Signal and Image processing

Journal Article

IEEE Transactions on Information Theory, ISSN 0018-9448, 02/2001, Volume 47, Issue 2, pp. 498 - 519

Algorithms that must deal with complicated global functions of many variables often exploit the manner in which the given functions factor as a product of "local" functions, each of which depends...

Graph theory | Graphical models | Sum-product algorithm | Viterbi algorithm | Forward/backward algorithm | Marginalization | Fast Fourier transform | Factor graphs | Kalman filtering | Iterative decoding | Tanner graphs | Belief propagation | sum-product algorithm | belief propagation | COMPUTER SCIENCE, INFORMATION SYSTEMS | fast Fourier transform | forward/backward algorithm | ENGINEERING, ELECTRICAL & ELECTRONIC | marginalization | iterative decoding | CODES | MODELS | graphical models | factor graphs | PROPAGATION | Algorithms | Fourier transformations | Functions | Research | Graphic methods | Iterative methods (Mathematics) | Networks | Fourier transforms | Mathematical analysis | Graphs | Mathematical models | Artificial intelligence | Information theory

Graph theory | Graphical models | Sum-product algorithm | Viterbi algorithm | Forward/backward algorithm | Marginalization | Fast Fourier transform | Factor graphs | Kalman filtering | Iterative decoding | Tanner graphs | Belief propagation | sum-product algorithm | belief propagation | COMPUTER SCIENCE, INFORMATION SYSTEMS | fast Fourier transform | forward/backward algorithm | ENGINEERING, ELECTRICAL & ELECTRONIC | marginalization | iterative decoding | CODES | MODELS | graphical models | factor graphs | PROPAGATION | Algorithms | Fourier transformations | Functions | Research | Graphic methods | Iterative methods (Mathematics) | Networks | Fourier transforms | Mathematical analysis | Graphs | Mathematical models | Artificial intelligence | Information theory

Journal Article

Advances in Computational Mathematics, ISSN 1019-7168, 4/2013, Volume 38, Issue 3, pp. 667 - 681

.... Several splitting algorithms recently proposed in the literature are recovered as special cases.

Monotone inclusion | Primal-dual algorithm | Cocoercivity | Numeric Computing | Theory of Computation | Duality | Monotone operator | Forward-backward algorithm | Algebra | Calculus of Variations and Optimal Control; Optimization | 90C25 | Computer Science | Composite operator | Operator splitting | 49M29 | Mathematics, general | 49M27 | 47H05 | MATHEMATICS, APPLIED | DECOMPOSITION | CONVEX MINIMIZATION PROBLEMS | VARIATIONAL-INEQUALITIES | CONVERGENCE | Duality theory (Mathematics) | Algorithms | Research | Monotonic functions | Operator theory | Operators | Splitting | Computation | Mathematical models | Inclusions | Sums

Monotone inclusion | Primal-dual algorithm | Cocoercivity | Numeric Computing | Theory of Computation | Duality | Monotone operator | Forward-backward algorithm | Algebra | Calculus of Variations and Optimal Control; Optimization | 90C25 | Computer Science | Composite operator | Operator splitting | 49M29 | Mathematics, general | 49M27 | 47H05 | MATHEMATICS, APPLIED | DECOMPOSITION | CONVEX MINIMIZATION PROBLEMS | VARIATIONAL-INEQUALITIES | CONVERGENCE | Duality theory (Mathematics) | Algorithms | Research | Monotonic functions | Operator theory | Operators | Splitting | Computation | Mathematical models | Inclusions | Sums

Journal Article

Journal of Mathematical Imaging and Vision, ISSN 0924-9907, 2/2015, Volume 51, Issue 2, pp. 311 - 325

In this paper, we propose an inertial forward-backward splitting algorithm to compute a zero of the sum of two monotone operators, with one of the two operators being co-coercive...

Mathematical Methods in Physics | Primal-dual algorithms | Monotone inclusions | Signal, Image and Speech Processing | Convex optimization | Computer Science | Image Processing and Computer Vision | Forward-backward splitting | Applications of Mathematics | Image restoration | Saddle-point problems | MATHEMATICS, APPLIED | THRESHOLDING ALGORITHM | PROXIMAL POINT ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | VARIATIONAL-INEQUALITIES | COMPUTER SCIENCE, SOFTWARE ENGINEERING | LINEAR INVERSE PROBLEMS | SPLITTING ALGORITHM | WEAK-CONVERGENCE | OPTIMIZATION | HILBERT-SPACE | OPERATORS | Graphics software | Algebra | Algorithms | Analysis

Mathematical Methods in Physics | Primal-dual algorithms | Monotone inclusions | Signal, Image and Speech Processing | Convex optimization | Computer Science | Image Processing and Computer Vision | Forward-backward splitting | Applications of Mathematics | Image restoration | Saddle-point problems | MATHEMATICS, APPLIED | THRESHOLDING ALGORITHM | PROXIMAL POINT ALGORITHM | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | VARIATIONAL-INEQUALITIES | COMPUTER SCIENCE, SOFTWARE ENGINEERING | LINEAR INVERSE PROBLEMS | SPLITTING ALGORITHM | WEAK-CONVERGENCE | OPTIMIZATION | HILBERT-SPACE | OPERATORS | Graphics software | Algebra | Algorithms | Analysis

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 3/2018, Volume 176, Issue 3, pp. 605 - 624

.... In this paper, we explore the behaviour of the algorithm when the inclusion problem has no solution...

Normal problem | 65K05 | Primary 47H09 | Mathematics | Theory of Computation | Optimization | Calculus of Variations and Optimal Control; Optimization | Operations Research/Decision Theory | Firmly nonexpansive mapping | Forward–backward splitting operator | 49M29 | 65K10 | 49M27 | 49N15 | Applications of Mathematics | Engineering, general | Secondary 47H05 | 47H14 | Attouch–Théra duality | Fixed point | MATHEMATICS, APPLIED | MAXIMALLY MONOTONE-OPERATORS | INCLUSIONS | Attouch-Thera duality | SIGNAL RECOVERY | DECOMPOSITION | SUM | PARAMONOTONICITY | SPACE | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | CONVERGENCE | MAPPINGS | DUALITY | Forward-backward splitting operator | Electrical engineering | Algorithms

Normal problem | 65K05 | Primary 47H09 | Mathematics | Theory of Computation | Optimization | Calculus of Variations and Optimal Control; Optimization | Operations Research/Decision Theory | Firmly nonexpansive mapping | Forward–backward splitting operator | 49M29 | 65K10 | 49M27 | 49N15 | Applications of Mathematics | Engineering, general | Secondary 47H05 | 47H14 | Attouch–Théra duality | Fixed point | MATHEMATICS, APPLIED | MAXIMALLY MONOTONE-OPERATORS | INCLUSIONS | Attouch-Thera duality | SIGNAL RECOVERY | DECOMPOSITION | SUM | PARAMONOTONICITY | SPACE | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | CONVERGENCE | MAPPINGS | DUALITY | Forward-backward splitting operator | Electrical engineering | Algorithms

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 10/2018, Volume 179, Issue 1, pp. 1 - 36

...–backward algorithms in the presence of perturbations, approximations, errors. These splitting algorithms aim to solve, by rapid methods, structured convex minimization problems...

FISTA | 65K05 | Mathematics | Theory of Computation | Tikhonov regularization | Optimization | Accelerated Nesterov method | Inertial forward–backward algorithms | Calculus of Variations and Optimal Control; Optimization | 90C25 | Operations Research/Decision Theory | Applications of Mathematics | Engineering, general | 49M37 | Perturbations | Structured convex optimization | MATHEMATICS, APPLIED | STABILIZATION | PROXIMAL POINT ALGORITHM | VISCOSITY | SPLITTING METHODS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | DYNAMICS | CONVERGENCE | Inertial forward-backward algorithms | MONOTONE-OPERATORS | Algorithms | Extrapolation | Approximation | Hilbert space | Coefficients | Regularization | Convergence | Optimization and Control

FISTA | 65K05 | Mathematics | Theory of Computation | Tikhonov regularization | Optimization | Accelerated Nesterov method | Inertial forward–backward algorithms | Calculus of Variations and Optimal Control; Optimization | 90C25 | Operations Research/Decision Theory | Applications of Mathematics | Engineering, general | 49M37 | Perturbations | Structured convex optimization | MATHEMATICS, APPLIED | STABILIZATION | PROXIMAL POINT ALGORITHM | VISCOSITY | SPLITTING METHODS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | DYNAMICS | CONVERGENCE | Inertial forward-backward algorithms | MONOTONE-OPERATORS | Algorithms | Extrapolation | Approximation | Hilbert space | Coefficients | Regularization | Convergence | Optimization and Control

Journal Article

Journal of Global Optimization, ISSN 0925-5001, 4/2019, Volume 73, Issue 4, pp. 801 - 824

In this paper, we first introduce a multi-step inertial Krasnosel’skiǐ–Mann algorithm (MiKM) for nonexpansive operators in real Hilbert spaces...

Nonexpansive operator | Monotone inclusion | Bounded perturbation resilience | Forward–backward splitting method | Mathematics | Optimization | Douglas–Rachford splitting method | Davis–Yin splitting method | Backward–forward splitting method | Operations Research/Decision Theory | Multi-step inertial Krasnosel’skiǐ–Mann algorithm | Computer Science, general | Real Functions | SUPERIORIZATION | MATHEMATICS, APPLIED | Forward-backward splitting method | Backward-forward splitting method | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | GRADIENT METHODS | Multi-step inertial Krasnosel'skii-Mann algorithm | Douglas-Rachford splitting method | Davis-Yin splitting method | Splitting | Hilbert space | Algorithms | Iterative methods | Convergence

Nonexpansive operator | Monotone inclusion | Bounded perturbation resilience | Forward–backward splitting method | Mathematics | Optimization | Douglas–Rachford splitting method | Davis–Yin splitting method | Backward–forward splitting method | Operations Research/Decision Theory | Multi-step inertial Krasnosel’skiǐ–Mann algorithm | Computer Science, general | Real Functions | SUPERIORIZATION | MATHEMATICS, APPLIED | Forward-backward splitting method | Backward-forward splitting method | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | GRADIENT METHODS | Multi-step inertial Krasnosel'skii-Mann algorithm | Douglas-Rachford splitting method | Davis-Yin splitting method | Splitting | Hilbert space | Algorithms | Iterative methods | Convergence

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 10/2016, Volume 171, Issue 1, pp. 90 - 120

...–Backward algorithm, involving two random maximal monotone operators and a sequence of decreasing step sizes...

Stochastic proximal point algorithm | Mathematics | Theory of Computation | Dynamical systems | Optimization | Random maximal monotone operators | Calculus of Variations and Optimal Control; Optimization | Stochastic Forward–Backward algorithm | Applications of Mathematics | Engineering, general | Operation Research/Decision Theory | 47H05 | 47N10 | 34A60 | 62L20 | MATHEMATICS, APPLIED | SUM | CONVEX-OPTIMIZATION | EQUIVALENCE | INTEGRALS | SEMIGROUPS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Stochastic Forward-Backward algorithm | CONVERGENCE | HILBERT-SPACE | Algorithms | Studies | Operators | Integrals | Asymptotic properties | Inequalities | Stochasticity | Convergence | Probability | Dynamical Systems | Optimization and Control

Stochastic proximal point algorithm | Mathematics | Theory of Computation | Dynamical systems | Optimization | Random maximal monotone operators | Calculus of Variations and Optimal Control; Optimization | Stochastic Forward–Backward algorithm | Applications of Mathematics | Engineering, general | Operation Research/Decision Theory | 47H05 | 47N10 | 34A60 | 62L20 | MATHEMATICS, APPLIED | SUM | CONVEX-OPTIMIZATION | EQUIVALENCE | INTEGRALS | SEMIGROUPS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Stochastic Forward-Backward algorithm | CONVERGENCE | HILBERT-SPACE | Algorithms | Studies | Operators | Integrals | Asymptotic properties | Inequalities | Stochasticity | Convergence | Probability | Dynamical Systems | Optimization and Control

Journal Article

SIAM Journal on Optimization, ISSN 1052-6234, 2013, Volume 23, Issue 3, pp. 1607 - 1633

.... Our analysis is based on the machinery of estimate sequences first introduced by Nesterov for the study of accelerated gradient descent algorithms...

Estimate sequences | Total variation | Accelerated forward-backward splitting | Inexact proximity operator | Convex optimization | MATHEMATICS, APPLIED | SIGNAL RECOVERY | PROXIMAL POINT ALGORITHM | accelerated forward-backward splitting | VARIABLE SELECTION | estimate sequences | LINEAR INVERSE PROBLEMS | IMAGE RECOVERY | inexact proximity operator | convex optimization | ANALYSE FONCTIONNELLE | RECOVERY PROBLEMS | CONVERGENCE | total variation | TOTAL VARIATION MINIMIZATION | CONVEX MINIMIZATION | Algorithms | Mathematical analysis | Computing costs | Exact solutions | Cost analysis | Estimates | Optimization | Convergence

Estimate sequences | Total variation | Accelerated forward-backward splitting | Inexact proximity operator | Convex optimization | MATHEMATICS, APPLIED | SIGNAL RECOVERY | PROXIMAL POINT ALGORITHM | accelerated forward-backward splitting | VARIABLE SELECTION | estimate sequences | LINEAR INVERSE PROBLEMS | IMAGE RECOVERY | inexact proximity operator | convex optimization | ANALYSE FONCTIONNELLE | RECOVERY PROBLEMS | CONVERGENCE | total variation | TOTAL VARIATION MINIMIZATION | CONVEX MINIMIZATION | Algorithms | Mathematical analysis | Computing costs | Exact solutions | Cost analysis | Estimates | Optimization | Convergence

Journal Article

Journal of Mathematical Analysis and Applications, ISSN 0022-247X, 07/2013, Volume 403, Issue 1, pp. 167 - 172

We propose an extended forward–backward algorithm for approximating a zero of a maximal monotone operator which can be split as the extended sum of two maximal monotone operators...

Extended sum | Splitting algorithm | Convergence in average | Maximal monotone operator | [formula omitted]-enlargement | Forward–backward algorithm | Projected subgradient algorithm | Forward-backward algorithm | ε-enlargement | MATHEMATICS, APPLIED | MAXIMAL MONOTONE-OPERATORS | SUMS | MATHEMATICS | ENLARGEMENTS | CONVERGENCE | epsilon-enlargement | Algorithms | Mathematics - Optimization and Control

Extended sum | Splitting algorithm | Convergence in average | Maximal monotone operator | [formula omitted]-enlargement | Forward–backward algorithm | Projected subgradient algorithm | Forward-backward algorithm | ε-enlargement | MATHEMATICS, APPLIED | MAXIMAL MONOTONE-OPERATORS | SUMS | MATHEMATICS | ENLARGEMENTS | CONVERGENCE | epsilon-enlargement | Algorithms | Mathematics - Optimization and Control

Journal Article

Journal of mathematical analysis and applications, ISSN 0022-247X, 01/2018, Volume 457, Issue 2, pp. 1095 - 1117

In this paper, we study the backward–forward algorithm as a splitting method to solve structured monotone inclusions, and convex minimization problems in Hilbert spaces...

Monotone inclusion | Proximal-gradient method | Forward–backward algorithm | Forward backward algorithm | MATHEMATICS, APPLIED | PROXIMAL POINT ALGORITHM | SUM | EXTRAGRADIENT | MATHEMATICS | ITERATION-COMPLEXITY | CONVERGENCE | NONCONVEX | CONVEX MINIMIZATION | SPLITTING METHOD | OPERATORS | Air forces | Algorithms

Monotone inclusion | Proximal-gradient method | Forward–backward algorithm | Forward backward algorithm | MATHEMATICS, APPLIED | PROXIMAL POINT ALGORITHM | SUM | EXTRAGRADIENT | MATHEMATICS | ITERATION-COMPLEXITY | CONVERGENCE | NONCONVEX | CONVEX MINIMIZATION | SPLITTING METHOD | OPERATORS | Air forces | Algorithms

Journal Article

SIAM Journal on Optimization, ISSN 1052-6234, 2018, Volume 28, Issue 4, pp. 2839 - 2871

Tseng's algorithm finds a zero of the sum of a maximally monotone operator and a monotone continuous operator by evaluating the latter twice per iteration...

Forward-backward splitting | Tseng’s splitting | Convex optimization | Monotone operator theory | Sequential algorithms | MATHEMATICS, APPLIED | monotone operator theory | forward-backward splitting | SPLITTING ALGORITHM | Tseng's splitting | convex optimization | CONVERGENCE | sequential algorithms

Forward-backward splitting | Tseng’s splitting | Convex optimization | Monotone operator theory | Sequential algorithms | MATHEMATICS, APPLIED | monotone operator theory | forward-backward splitting | SPLITTING ALGORITHM | Tseng's splitting | convex optimization | CONVERGENCE | sequential algorithms

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 2015, Volume 164, Issue 3, pp. 993 - 1025

We propose a splitting algorithm for solving a coupled system of primal-dual monotone inclusions in real Hilbert spaces...

Monotone inclusion | Coupled system | Cocoercivity | Composite operator | Operator splitting | Duality | Monotone operator | Forward–backward algorithm | Primal–dual algorithm | MATHEMATICS, APPLIED | Primal-dual algorithm | SIGNAL RECOVERY | DECOMPOSITION | PROXIMAL POINT ALGORITHM | Forward-backward algorithm | COMPOSITE | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | CONVERGENCE | Algorithms | Studies | Operations research | Hilbert space | Mathematical models | Formulations | Operators | Splitting | Joining | Representations | Inclusions | Optimization | Convergence

Monotone inclusion | Coupled system | Cocoercivity | Composite operator | Operator splitting | Duality | Monotone operator | Forward–backward algorithm | Primal–dual algorithm | MATHEMATICS, APPLIED | Primal-dual algorithm | SIGNAL RECOVERY | DECOMPOSITION | PROXIMAL POINT ALGORITHM | Forward-backward algorithm | COMPOSITE | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | CONVERGENCE | Algorithms | Studies | Operations research | Hilbert space | Mathematical models | Formulations | Operators | Splitting | Joining | Representations | Inclusions | Optimization | Convergence

Journal Article

International Journal of Production Economics, ISSN 0925-5273, 2009, Volume 117, Issue 2, pp. 302 - 316

.... In this paper, we focus on this problem and develop a hybrid Genetic Algorithm (MM-HGA) to solve it. Its main contributions are the mode assignment procedure, the fitness function and the use of a very efficient improving method...

Renewable and non-renewable resources | Project management and scheduling | Multimode forward–backward improving method | Genetic Algorithms | Multimode forward-backward improving method | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | CLASSIFICATION | RESTRICTIONS | ENGINEERING, MANUFACTURING | ENGINEERING, INDUSTRIAL | HEURISTICS | Project management and scheduling Renewable and non-renewable resources Genetic Algorithms Multimode forward-backward improving method | Genetic research | Algorithms | Executions and executioners

Renewable and non-renewable resources | Project management and scheduling | Multimode forward–backward improving method | Genetic Algorithms | Multimode forward-backward improving method | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | CLASSIFICATION | RESTRICTIONS | ENGINEERING, MANUFACTURING | ENGINEERING, INDUSTRIAL | HEURISTICS | Project management and scheduling Renewable and non-renewable resources Genetic Algorithms Multimode forward-backward improving method | Genetic research | Algorithms | Executions and executioners

Journal Article