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Production and Delivery Batch Scheduling with Multiple Due Dates to Minimize Total Cost

JOURNAL OF ENGINEERING AND TECHNOLOGICAL SCIENCES 2017年第1期49卷 16-36页

作者： Prasetyaningsih, Endang Suprayogi, Suprayogi Samadhi, T. M. A. Ari Halim, Abdul Hakim Inst Teknol Bandung Fac Ind Technol Dept Ind Engn & Management Jalan Ganesha 10 Bandung 40132 Indonesia

This paper addresses an integrated production and delivery batch scheduling problem for a make-to-order environment over daily time period, where the holding costs of in-process and completed parts at a supplier location and of completed parts at a manufacturer location are distinguished. All orders of parts with different due dates from the manufacturer arrive at the same time. The parts are produced in production batches and subsequently the completed parts are delivered in delivery batches using a capacitated vehicle in order to be received at the respective due dates. This study was aimed at finding an integrated schedule of production and delivery batches so as to meet the due date at minimum total cost consisting of the corresponding holding cost and delivery cost. The holding cost is a derivation of the so-called actual flow time (AFT), while the delivery cost is assumed to be proportional to the number of deliveries. The problems can be formulated as an integer non-linear programming model, and the global optimal solution can be obtained using optimization software. A heuristic algorithm is proposed to cope with the computational time problem using software. The numerical experiences show that the proposed algorithm yields near global optimal solutions.

关键词： actual flow time backward scheduling batch scheduling integer nonlinear programming integrated production and delivery

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Optimizing nurse capacity in a teaching hospital neonatal intensive care unit

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HEALTH CARE MANAGEMENT SCIENCE 2017年第2期20卷 276-285页

作者： Kokangul, Ali Akcan, Serap Narli, Mufide Cukurova Univ Dept Ind Engn TR-01330 Adana Turkey Aksaray Univ Dept Ind Engn TR-68100 Aksaray Turkey

Patients in intensive care units need special attention. Therefore, nurses are one of the most important resources in a neonatal intensive care unit. These nurses are required to have highly specialized training. The random number of patient arrivals, rejections, or transfers due to lack of capacity (such as nurse, equipment, bed etc.) and the random length of stays, make advanced knowledge of the optimal nurse a requirement, for levels of the unit behave as a stochastic process. This stochastic nature creates difficulties in finding optimal nurse staffing levels. In this paper, a stochastic approximation which is based on the required nurse: patient ratio and the number of patients in a neonatal intensive care unit of a teaching hospital, has been developed. First, a meta-model was built to generate simulation results under various numbers of nurses. Then, those experimented data were used to obtain the mathematical relationship between inputs (number of nurses at each level) and performance measures (admission number, occupation rate, and satisfaction rate) using statistical regression analysis. Finally, several integer nonlinear mathematical models were proposed to find optimal nurse capacity subject to the targeted levels on multiple performance measures. The proposed approximation was applied to a Neonatal Intensive Care Unit of a large hospital and the obtained results were investigated.

关键词： Nurse capacity Optimization Simulation meta modeling integer nonlinear programming Neonatal intensive care

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Hybrid Algorithms Based on integer programming for the Search of Prioritized Test Data in Software Product Lines 20th

Hybrid Algorithms Based on Integer Programming for the Searc...

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20th European Conference on the Applications of Evolutionary Computation (EvoApplications)

作者： Ferrer, Javier Chicano, Francisco Alba, Enrique Univ Malaga Malaga Spain

ISBN: (纸本)9783319557922;9783319557915

In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using integer programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of-the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work.

关键词： Combinatorial Interaction Testing Software Product Lines Pairwise testing Feature models integer Linear programming integer nonlinear programming Prioritization

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A metaheuristic framework for nonlinear Capacitated Covering Problems

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OPTIMIZATION LETTERS 2016年第1期10卷 169-180页

作者： Malaguti, Enrico Medina Duran, Rosa Toth, Paolo Univ Bologna DEI I-40136 Bologna Italy Univ Concepcion Fac Ingn Dept Ingn Ind Concepcion Chile

Several relevant optimization problems can be formulated as generalizations of Capacitated Covering Problems, by considering a cost function that combines a linear term with a nonlinear one. In this paper we introduce the Staircase Capacitated Covering Problem, where the nonlinear term has a staircase shape, and we propose a framework based on a Metaheuristic algorithm for solving problems having this formulation. The performance of the Metaheuristic algorithm in solving the Staircase Capacitated Covering Problem is evaluated on a set of instances derived from an industrial application, and it is compared with a linearized formulation of the problem solved by CPLEX. In particular, the experiments show that the former produces better solutions in the same computing time.

关键词： integer nonlinear programming Capacitated Covering Problems Metaheuristic algorithm

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Controlling posterior producer and consumer risks in lot reinspection

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APPLIED MATHEMATICAL MODELLING 2016年第23-24期40卷 10760-10770页

作者： Fernandez, Arturo J. Univ La Laguna Dept Matemat Estadist & Invest Operat Tenerife 38071 Canary Islands Spain

Assuming that maximum tolerable posterior risks are specified for both producer and consumer, an integer nonlinear programming problem is formulated and solved in order to determine the optimal defects-per-unit acceptance sampling plan when lots found unacceptable may be resubmitted for reinspection. The number of nonconformities per inspected item follows a Poisson distribution. A computational algorithm is proposed to solve the underlying constrained minimization problem. The suggested procedure simplifies and quickens the determination of the inspection scheme for resubmitted lot acceptance with limited posterior risks that minimizes the expected number of sampled items per lot. An application to the manufacturing of paper is considered to illustrate the methodology developed. The generalized truncated gamma distribution is used to describe the prior uncertainty about the incoming defect rate per unit. The degree of similarity between the available previous information and the current study is 'also evaluated. Suitable ways are provided to assume a reduced parameter space for the defect rate and to update the prior model using past performance of the acceptance plan. The incorporation of lot resubmissions, as well as previous defect count data and expert opinions, into the decision process often yields appreciable savings in sampling effort. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Constrained optimization Generalized truncated gamma model Quality control integer nonlinear programming Poisson defect rate

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Regulatory Networks of integer nonlinear programming(RNINLP): a Model to Analyze Gene Regulatory Networks of Breast Cancer Metastasis

Regulatory Networks of Integer Nonlinear Programming(RNINLP)...

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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Luo, Wanchun Gong, Lihong Ren, Kaichun Yi, Dong Third Mil Med Univ Dept Med Stat Chongqing 400038 Peoples R China Third Mil Med Univ Coll Biomed Engn & Med Imaging Dept Math & Biomath Chongqing 400038 Peoples R China Chongqing Commun Coll Dept Machine & Elect Chongqing 400035 Peoples R China

ISBN: (纸本)9781424467129

There are more and more data from Human Genome Project that we need better methods to deal with. Some mathematical models have been presented to analyze gene regulatory networks, such as Boolean networks Bayesian networks, differential equation, weight matrices, etc. Some of the models could describe some rules of the genetic regulatory relations properly, such as Bayesian networks, differential equation, but the rest did not work very well. It is thus necessary to consider some new mathematical models to estimate the gene regulatory relations according to some experimental data. Here we have utilized the entropy information from gene data of breast cancer metastasis to get the weights of all the genes, and set up a RNINLP model in which minimum error is regarded as objective function to search for the regulatory relation in the genes, and then sieved regulatory genes by coefficient correlation model. Using the programs of LINGO8.0 and MATLAB7.0, we got a gene regulatory network of the 27 genes related to the breast cancer metastasis. We found that there were 25 pairs of genes exiting regulatory relation and 11 pairs of genes being mutual promotion effect. RNINLP utilizes almost all the information of the data, so it can describe the regulatory relation of genes with coefficient correlation model, and the model can be extended to even more complicated gene regulatory networks.

关键词： integer nonlinear programming gene regulatory networks breast cancer metastasis

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Agile control of CO2capture technology for maximum net operating revenue

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IFAC-PapersOnLine 2016年第7期49卷 332-335页

作者： Manaf, Norhuda Abdul Qadir, Abdul Abbas, Ali School of Chemical and Biomolecular Engineering The University of Sydney Sydney2006 Australia

This paper uses a multi-layered control scheme consisting of model predictive control (MPC) and mixed integer non-linear programming (MINLP) for the analysis of power plant net operating revenue when retrofitted with a post-combustion carbon capture (PCC) plant. The capability of the proposed control scheme is examined for 24-hour operations of an integrated plant (power plant with PCC) in the years 2011 and 2020. The control scheme is tested in response to variability in upstream power plant dynamic loads. The agility of the control scheme subject to forecast 2020 electricity and carbon prices is shown to result in yearly net operating revenue of approximately 12% of the gross revenue. Whereas, the same integrated plant generates a net operating revenue loss of roughly 13% of the gross revenue under 2011 electricity and carbon prices. © 2016

关键词： Predictive control systems Algorithms Automation Dynamic loads integer programming MIMO systems Model predictive control Multiplexing equipment nonlinear programming nonlinear systems Close loop Integrated plants Mixed integer nonlinear programming Multi input multi output systems Operating revenues Plant wides Post combustion carbon captures Power plant dynamics

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Parallel Induction of Nondeterministic Finite Automata 11th

Parallel Induction of Nondeterministic Finite Automata

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11th International Conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Jastrzab, Tomasz Czech, Zbigniew J. Wieczorek, Wojciech Silesian Tech Univ Inst Informat Gliwice Poland Univ Silesia Inst Informat Sosnowiec Poland

ISBN: (纸本)9783319321493;9783319321486

The induction of a minimal nondeterministic finite automaton (NFA) consistent with a given set of examples and counter examples, which is known to be computationally hard, is discussed. The paper is an extension to the novel approach of transforming the problem of NFA induction into the integer nonlinear programming (INLP) problem. An improved formulation of the problem is proposed along with the two parallel algorithms to solve it. The methods for the distribution of tasks among processors along with distributed termination detection are presented. The experimental results for selected benchmarks are also reported.

关键词： Parallel algorithms Nondeterministic finite automata integer nonlinear programming

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A new bi-objective model for a closed-loop supply chain problem with inventory and transportation times

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SCIENTIA IRANICA 2016年第3期23卷 1441-1458页

作者： Forouzanfar, F. Tavakkoli-Moghaddam, R. Bashiri, M. Baboli, A. Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Univ Tehran Coll Engn Ctr Excellence Intelligence Based Expt Mech Tehran Iran Shahed Univ Dept Ind Engn Fac Engn Tehran Iran INSA Lyon DISP Lab F-69621 Villeurbanne France

This paper considers a closed-loop supply chain design problem including several producers, distributors, customers, collecting centers, recycle centers, revival centers, raw materials customers considering several periods, existing inventory and shortage in distribution centers, and transportation cost and time. This problem is formulated as a bi-objective integer nonlinear programming model. The aim of this model is to determine numbers and locations of supply chain elements, their capacity levels, allocation structure, mode of transportation between them, amount of transported products between them, amount of existing inventory, and shortage in distribution centers in each period to minimize the sum of system costs and transportation time in the network. To validate this model and show the applicability of it for small-sized problems, GAMS software is used. Because this given problem is NP-hard, a Bee Colony Optimization (BCO) algorithm is proposed to solve medium and large-sized problems. Furthermore, to examine the efficiency of the proposed BCO algorithm, the associated results are compared with the results obtained by the Genetic Algorithm (GA). Finally, the conclusion is provided. (C) 2016 Sharif University of Technology. All rights reserved.

关键词： Closed-loop supply chain integer nonlinear programming Transportation Inventory Bee algorithm

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Optimal coordination of directional overcurrent relays in distribution systems based on network splitting

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2015年第10期25卷 2310-2324页

作者： Azari, Afshin Akhbari, Mahdi Tehran Power Transmiss Maintenance Engn METANIR C Tehran *** Iran Shahed Univ Fac Engn Tehran *** Iran

In real case of distribution systems with several directional overcurrent relays, the designer is facing an optimization problem with an extensive search space of discrete values. Finding the optimal solution to such a problem is a time-consuming task with big chance of nonconvexity. In this paper, the optimal coordination of directional overcurrent relays in distribution systems is modeled by attempting the practical issues, that is, full discrete variables for time-current curve, time multiplier setting, and plug setting. To reduce the calculation time, the problem is solved by using a novel method based on network splitting. The problem is solved in two stages: the first one finds the optimal solution for the subnetworks individually and the second one determines the optimal setting for the relays on the tie lines connecting the subnetworks. It is shown that the proposed method improves the relays' operating times and also reduces the chance of nonconvexity of the problem. By applying the proposed method to the 30-bus Institute of Electrical and Electronics Engineers test system, the results are compared with the conventional algorithms. It is found how the practical issues related to the relay characteristics selection can affect the overall relays' time. Also, the computation time is considerably reduced with network splitting method presented in this paper. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： directional overcurrent relay optimal coordination genetic algorithm integer nonlinear programming

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