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1 – 10 of 279U. Dinesh Kumar and J. Knezevic
Proposes optimization models for spare provisioning. In the first model, considers a series system with m components where each component can have a maximum of (n‐1) spares. The…
Abstract
Proposes optimization models for spare provisioning. In the first model, considers a series system with m components where each component can have a maximum of (n‐1) spares. The objective function is to maximize the availability of the system satisfying a constraint on space required for the spares. In the second model, considers a series‐parallel system where each component of the system can have a maximum of (n‐1) spares. The optimization models developed in the paper can be solved using general purpose software such as SOLVER of EXCEL. Also presents an efficient branch and bound algorithm which can be used to solve the optimization problem.
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To discuss a new parallel algorithmic platform (minlp_machine) for complex mixed‐integer non‐linear programming (MINLP) problems.
Abstract
Purpose
To discuss a new parallel algorithmic platform (minlp_machine) for complex mixed‐integer non‐linear programming (MINLP) problems.
Design/methodology/approach
The platform combines features from classical non‐linear optimization methodology with novel innovations in computational techniques. The system constructs discrete search zones around noninteger discrete‐valued variables at local solutions, which simplifies the local optimization problems and reduces the search process significantly. In complicated problems fast feasibility restoration may be achieved through concentrated Hessians. The system is programmed in strict ANSI C and can be run either stand alone or as a support library for other programs. File I/O is designed to recognize possible usage in both single and parallel processor environments. The system has been tested on Alpha, Sun and Linux mainframes and parallel IBM and Cray XT4 supercomputer environments. The constrained problem can, for example, be solved through a sequence of first order Taylor approximations of the non‐linear constraints and feasibility restoration utilizing Hessian information of the Lagrangian of the MINLP problem, or by invoking a nonlinear solver like SQP directly in the branch and bound tree. minlp_machine( ) has been tested as a support library to genetic hybrid algorithm (GHA). The GHA(minlp_machine) platform can be used to accelerate the performance of any linear or non‐linear node solver. The paper introduces a novel multicomputer partitioning of the discrete search space of genuine MINLP‐problems.
Findings
The system is successfully tested on a small sample of representative MINLP problems. The paper demonstrates that – through concurrent nonlinear branch and bound search – minlp_machine( ) outperforms some recent competing approaches with respect to the number of nodes in the branch and bound tree. Through parallel processing, the computational complexity of the local optimization problems is reduced considerably, an important aspect for practical applications.
Originality/value
This paper shows that binary‐valued MINLP‐problems will reduce to a vector of ordinary non‐linear programming on a suitably sized mesh. Correspondingly, INLP‐ and ILP‐problems will require no quasi‐Newton steps or simplex iterations on a compatible mesh.
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Stéphane Brisset and Tuan-Vu Tran
This paper aims to propose a multiobjective branch and bound (MOBB) algorithm with a new criteria for the branching and discarding of nodes based on Pareto dominance and…
Abstract
Purpose
This paper aims to propose a multiobjective branch and bound (MOBB) algorithm with a new criteria for the branching and discarding of nodes based on Pareto dominance and contribution metric.
Design/methodology/approach
A multiobjective branch and bound (MOBB) method is presented and applied to the bi-objective combinatorial optimization of a safety transformer. A comparison with exhaustive enumeration and non-dominated sorting genetic algorithm (NSGA2) confirms the solutions.
Findings
It appears that MOBB and NSGA2 are both sensitive to their control parameters. The parameters for the MOBB algorithm are the number of starting points and the number of solutions on the relaxed Pareto front. The parameters of NSGA2 are the population size and the number of generations.
Originality/value
The comparison with exhaustive enumeration confirms that the proposed algorithm is able to find the complete set of non-dominated solutions in about 235 times fewer evaluations. As this last method is exact, its confidence level is higher.
Details
Keywords
To propose a new algorithmic platform (minlp_machine) for complex mixed‐integer non‐linear programming (MINLP) problems.
Abstract
Purpose
To propose a new algorithmic platform (minlp_machine) for complex mixed‐integer non‐linear programming (MINLP) problems.
Design/methodology/approach
The platform combines features from classical non‐linear optimization methodology with novel innovations in computational techniques. The system constructs discrete search zones around non‐integer discrete‐valued variables of local solutions, which reduces the search process significantly. In complicated problems fast feasibility restoration is achieved through concentrated Hessians. The system is programmed in strict ANSI C and can be run either stand alone or as a support library for other programs. File I/O is designed to recognize possible usage in both single and parallel processor environments.
Findings
The system has been tested on Alpha and Sun mainframes and – as a support library for a Genetic Hybrid Algorithm (GHA()) – in Linux and IBM parallel supercomputer environments. The constrained problem can, for example, be solved through a sequence of first order Taylor approximations of the non‐linear constraints and occasional feasibility restoration through Hessian information of the Lagrangian of the MINLP problem, or by invoking a nonlinear solver like SQP directly in the branch and bound tree. The system has been successfully tested on a small sample of representative continuous‐valued non‐linear programming problems.
Originality/value
It is demonstrated that – through zone‐constrained search – minlp_machine() outperforms some recent competing approaches with respect to the number of nodes in the branch and bound tree.
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Suggests that, in recent years, remarkable progress has been madein the development of the topological design of logistics networks,especially in the warehouse location problem…
Abstract
Suggests that, in recent years, remarkable progress has been made in the development of the topological design of logistics networks, especially in the warehouse location problem. Extends the standard warehouse location problem to a generalization of multiproduct capacitated warehouse location problem, as opposed to differentiated variations of a single‐product warehouse location problem, where each warehouse has a given capacity for carrying each product. Presents an algorithm based on cross‐decomposition, to reduce the computational difficulty by incorporating Benders decomposition and Lagrangean relaxation. Computational results of this algorithm are encouraging.
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Abdelbasset Barkat, Kazar Okba and Samir Bourekkache
User requests over the cloud are not achievable with one single service, multiple services need to be executed to fulfill what a user asks for. Typically, such services are…
Abstract
Purpose
User requests over the cloud are not achievable with one single service, multiple services need to be executed to fulfill what a user asks for. Typically, such services are composed and presented as one global service. Moreover, the same operation can be achieved by multiple services available at different clouds, which can result in different possibilities in composing them. This paper aims to decrease the number of clouds involved in the composition process, so that user requests are satisfied with minimal cost (communication costs, execution time and financial charges).
Design/methodology/approach
This paper investigates the use of an intelligent water drops (IWDs) optimization-based algorithm, and an integer linear programming model to optimize the number of cloud bases involved in the composition process. A comparison of the solutions found by these two techniques is presented in the paper.
Findings
The obtained results show that the number of cloud bases can be decreased without affecting user satisfaction.
Originality/value
The paper is a first attempt to use the IWDs algorithm for service composition, tested with big-size data.
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Dmitry Samarkanov, Frédéric Gillon, Pascal Brochet and Daniel Laloy
The purpose of this paper is to present two optimization methodologies based on interval branch‐and‐bound algorithm.
Abstract
Purpose
The purpose of this paper is to present two optimization methodologies based on interval branch‐and‐bound algorithm.
Design/methodology/approach
These techniques decrease the total time of computation, even in spite of discrete nature of some of the design variables. Computational experiments performed on multivariable optimization problem reveal great accuracy and technical validity of developed approaches. As an example, the optimal design of the induction machine (IM) was treated, where the aim was to find the set of the most efficient and, at the same time, cheapest in the manufacturing configurations.
Findings
In this paper, two approaches were developed for resolving the problem of optimal design of IM with discrete variables. The strategy of constructing the meta‐models is utilized and put in practice. The methods show relatively high efficiency and robustness of obtained results.
Originality/value
These approaches are the core technics of the developed industrial application, which help identify the set of optimal configurations of IM with the criteria of optimality such as total cost of manufacturing and the efficiency of IM.
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A comprehensive review of the literature for the problem oflot‐size scheduling (serial and assembly) considering the uncapacitatedproblem and complicated capacitated assembly…
Abstract
A comprehensive review of the literature for the problem of lot‐size scheduling (serial and assembly) considering the uncapacitated problem and complicated capacitated assembly manufacturing structure. Analyses the different solution techniques and findings for each product set.
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Sang M. Lee and Lori Sharp Franz
The location‐allocation problem involves multiple shipping destinations, with known demands for a given product and known transportation costs from sources to destinations. The…
Abstract
The location‐allocation problem involves multiple shipping destinations, with known demands for a given product and known transportation costs from sources to destinations. The problem is to determine the number of facilities and their locations in order to best service the shipping destinations. This paper presents an approach to facility location which allows the analysis of multiple conflicting goals as an extension of previous solution approaches. Specifically, the paper applies the branch and bound integer goal programming approach to the location‐allocation problem.
B.V. Babu, Pallavi G. Chakole and J.H. Syed Mubeen
This paper presents the application of Differential Evolution (DE), an evolutionary computation technique for the optimal design of gas transmission network. As a gas transmission…
Abstract
This paper presents the application of Differential Evolution (DE), an evolutionary computation technique for the optimal design of gas transmission network. As a gas transmission system includes source of gas, delivery sites with pipeline segments and compressors, the design of efficient and economical network involves lot of parameters. In addition, there are many equality and inequality constraints to be satisfied making the problem highly non‐linear. Hence an efficient strategy is needed in searching for the global optimum. In this study, DE has been successfully applied for optimal design of gas transmission network. The results obtained are compared with those of nonlinear programming technique and branch and bound algorithm. DE is able to find an optimal solution with a cost that is less than reported in the earlier literature. The proposed strategy takes less computational time to converge when compared to the existing techniques without compromising with the accuracy of the parameter estimates.
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