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On the Transformation Mechanism for Formulating a Multiproduct Two-Layer Supply Chain Network Design Problem as a Network Flow Model

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-13页

作者： Gan, Mi Li, Zongping Chen, Si Southwest Jiaotong Univ Sch Transportat Traff & Logist Chengdu 610031 Sichuan Peoples R China

The multiproduct two-layer supply chain is very common in various industries. In this paper, we introduce a possible modeling and algorithms to solve a multiproduct two-layer supply chain network design problem. The decisions involved are the DCs location and capacity design decision and the initial distribution planning decision. First we describe the problem and give a mixed integer programming (MIP) model;such problem is NP-hard and it is not easy to reduce the complexity. Inspired by it, we develop a transformation mechanism of relaxing the fixed cost and adding some virtual nodes and arcs to the original network. Thus, a network flow problem (NFP) corresponding to the original problem has been formulated. Given that we could solve the NFP as a minimal cost flow problem. The solution procedures and network simplex algorithm(INS) are discussed. To verify the effectiveness and efficiency of the model and algorithms, the performance measure experimental has been conducted. The experiments and result showed that comparing with MIP model solved by genetic algorithm (GA) and Benders, decomposition algorithm (BD) the NFP model and INS are also effective and even more efficient for both small-scale and large-scale problems.

关键词： MULTIPRODUCT firms SUPPLY chains PROBLEM solving mixed integer linear programming GENETIC algorithms

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Scheduling job families on non-identical parallel machines with time constraints

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ANNALS OF OPERATIONS RESEARCH 2014年第1期213卷 221-234页

作者： Obeid, Ali Dauzere-Peres, Stephane Yugma, Claude Ecole Mines St Etienne Ctr Microelect Provence F-13541 Gardanne France

This paper studies the scheduling of lots (jobs) of different product types (job family) on parallel machines, where not all machines are able to process all job families (non-identical machines). A special time constraint, associated to each job family, should be satisfied for a machine to remain qualified for processing a job family. This constraint imposes that the time between the executions of two consecutive jobs of the same family on a qualified machine must not exceed the time threshold of the family. Otherwise, the machine becomes disqualified. This problem comes from semiconductor manufacturing, when Advanced Process Control constraints are considered in scheduling problems. To solve this problem, two mixed integer linear programming models are proposed that use different types of variables. Numerical experiments show that the second model is much more effective, and that there is a trade-off between optimizing the scheduling objective and maximizing the number of machines that remain qualified for the job families. Two heuristics are also presented and studied in the numerical experiments.

关键词： Scheduling Parallel machines Time constraint mixed integer linear programming Heuristics Semiconductor manufacturing

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Use of model predictive control for experimental microgrid optimization

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APPLIED ENERGY 2014年 115卷 37-46页

作者： Parisio, Alessandra Rikos, Evangelos Tzamalis, George Glielmo, Luigi KTH Royal Inst Technol ACCESS Linnaeus Ctr Stockholm Sweden KTH Royal Inst Technol Sch Elect Engn Automat Control Lab Stockholm Sweden Ctr Renewable Energy Sources & Saving CRES Dept PVs & DERs Syst Athens Greece Ctr Renewable Energy Sources & Saving CRES Dept RES & Hydrogen Technol Athens Greece Univ Sannio Dept Engn Benevento Italy

In this paper we deal with the problem of efficiently optimizing microgrid operations while satisfying a time-varying request and operation constraints. Microgrids are subsystems of the distribution grid comprising sufficient generating resources to operate in isolation from the main grid, in a deliberate and controlled way. The Model Predictive Control (MPC) approach is applied for achieving economic efficiency in microgrid operation management. The method is thus applied to an experimental microgrid located in Athens, Greece: experimental results show the feasibility and the effectiveness of the proposed approach. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Model predictive control Microgrids Optimization mixed integer linear programming

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Optimality-based bound contraction with multiparametric disaggregation for the global optimization of mixed-integer bilinear problems

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JOURNAL OF GLOBAL OPTIMIZATION 2014年第2-3期59卷 277-306页

作者： Castro, Pedro M. Grossmann, Ignacio E. Lab Nacl Energia & Geol P-1649038 Lisbon Portugal Univ Lisbon Fac Ciencias Ctr Invest Operac P-1749016 Lisbon Portugal Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

We address nonconvex mixed-integer bilinear problems where the main challenge is the computation of a tight upper bound for the objective function to be maximized. This can be obtained by using the recently developed concept of multiparametric disaggregation following the solution of a mixed-integer linear relaxation of the bilinear problem. Besides showing that it can provide tighter bounds than a commercial global optimization solver within a given computational time, we propose to also take advantage of the relaxed formulation for contracting the variables domain and further reduce the optimality gap. Through the solution of a real-life case study from a hydroelectric power system, we show that this can be an efficient approach depending on the problem size. The relaxed formulation from multiparametric formulation is provided for a generic numeric representation system featuring a base between 2 (binary) and 10 (decimal).

关键词： Global optimization mixed integer nonlinear programming mixed integer linear programming Scheduling Hydroelectric system

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Simultaneous production and distribution of industrial gas supply-chains

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COMPUTERS & CHEMICAL ENGINEERING 2014年 69卷 39-58页

作者： Marchetti, Pablo A. Gupta, Vijay Grossmann, Ignacio E. Cook, Lauren Valton, Pierre-Marie Singh, Tejinder Li, Tong Andre, Jean Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA Amer Air Liquide Inc Delaware Res & Technol Ctr Newark DE 19702 USA Air Liquide Paris Saclay R&D Ctr F-78350 Jouy En Josas France

In this paper, we propose a multi-period mixed-integer linear programming model for optimal enterpriselevel planning of industrial gas operations. The objective is to minimize the total cost of production and distribution of liquid products by coordinating production decisions at multiple plants and distribution decisions at multiple depots. Production decisions include production modes and rates that determine power consumption. Distribution decisions involve source, destination, quantity, route, and time of each truck delivery. The selection of routes is a critical factor of the distribution cost. The main goal of this contribution is to assess the benefits of optimal coordination of production and distribution. The proposed methodology has been tested on small, medium, and large size examples. The results show that significant benefits can be obtained with higher coordination among plants/depots in order to fulfill a common set of shared customer demands. The application to real industrial size test cases is also discussed. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Supply-chain optimization Industrial gases Production planning Inventory routing problem Multi period model mixed integer linear programming

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Short-term hydropower optimal scheduling considering the optimization of water time delay

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ELECTRIC POWER SYSTEMS RESEARCH 2014年第May期110卷 188-197页

作者： Ge, Xiao-lin Zhang, Li-zi Shu, Jun Xu, Nai-fan Shanghai Univ Elect Power Coll Elect Engn Shanghai 200090 Peoples R China North China Elect Power Univ Sch Elect & Elect Engn Beijing 102206 Peoples R China Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

This paper is proposed to develop a novel mixed-integer model to solve the short-term hydropower optimal scheduling problem. The model is designed with consideration of the optimization of water time delay. The water time delay is the time required for discharging water from upstream reservoir to its downstream reservoir. It is always in change, which makes a real challenge to handle the corresponding mathematical models. In order to develop the model, we formulate water time delay as a nonlinear function of the outflow from upstream reservoir, which can describe the coupling of hydraulic and electric among cascaded hydropower stations accurately. Meanwhile, the complicated head-sensitive water-to-power conversion and piecewise output limits are also taken into account. To overcome the difficulty of solving the mixed-integer nonlinear optimization problem, the formulation above is converted into a mixed integer linear programming (MILP) problem in terms of integer algebra techniques. The applied commercial software is called CPLEX, which can solve the related MILP problem successfully. Based on a case study with 13 reservoirs and 44 hydropower units, the study shows that the proposed model with water-time-delay can improve the operability and economic benefits of scheduling. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Hydropower stations Optimal scheduling mixed integer linear programming Water time delay linear modeling

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DESIGNING DISCRETE SEQUENTIAL TESTS VIA mixed integer programming

DESIGNING DISCRETE SEQUENTIAL TESTS VIA MIXED INTEGER PROGRA...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Michael Fauss Abdelhak M. Zoubir Signal Processing Group Technische Universitat Darmstadt Merckstrasse 25 64283 Darmstadt Germany

ISBN: (纸本)9781479928941

We show that the optimal design of non-randomized discrete sequential tests, i.e., tests whose test statistics take on only a countable number of states, can be modeled as a mixed integer linear problem. This is done by reformulating the difference equations describing the random walk on the integer lattice in terms of linear mixed integer constraints. We outline the general procedure and give a simple example to show how the proposed method can be used in practice.

关键词： programming Difference equation Random walk mixed integer Optimal design mixed integer linear programming Mixing

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Model and Method for Multiobjective Time-Dependent Hazardous Material Transportation

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-11页

作者： Zhou, Zhen Che, Ada Chu, Feng Chu, Chengbin Northwestern Polytech Univ Sch Management Xian 710072 Shaanxi Peoples R China Univ Evry Val Essonne Lab Informat Biol Integrat & Syst Complexes F-91020 Evry France Ecole Cent Paris Lab Genie Ind F-92295 Chatenay Malabry France

In most of the hazardous material transportation problems, risk factors are assumed to be constant, which ignores the fact that they can vary with time throughout the day. In this paper, we deal with a novel time-dependent hazardous material transportation problem via lane reservation, in which the dynamic nature of transportation risk in the real-life traffic environment is taken into account. We first develop a multiobjective mixed integer programming (MIP) model with two conflicting objectives: minimizing the impact on the normal traffic resulting from lane reservation and minimizing the total transportation risk. We then present a cut-and-solve based epsilon-constraint method to solve this model. Computational results indicate that our method outperforms the epsilon-constraint method based on optimization software package CPLEX.

关键词： TRANSPORTATION TIME series analysis HAZARDOUS substances PROBLEM solving mixed integer linear programming COMPUTER software

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A Lagrangian heuristic for sprint planning in agile software development

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COMPUTERS & OPERATIONS RESEARCH 2014年第Mar.期43卷 116-128页

作者： Boschetti, Marco A. Golfarelli, Matteo Rizzi, Stefano Turricchia, Elisa Univ Bologna Dept Math I-47521 Cesena Italy Univ Bologna DISI I-40126 Bologna Italy

Agile methods for software development promote iterative design and implementation. Most of them divide a project into functionalities, called user stories;at each iteration, often called a sprint, a subset of user stories are developed. The sprint planning phase is critical to ensure the project success, but it is also a difficult problem because several factors impact on the optimality of a sprint plan, e.g., the estimated complexity, business value, and affinity of the user stories to be included in each sprint. In this paper we present an approach for sprint planning based on an integer linear programming model. Given the estimates made by the project team and a set of development constraints, the optimal solution of the model is a sprint plan that maximizes the business value perceived by users. Solving to optimality the model by a general-purpose MIP solver, such as IBM llog Cplex, takes time and for some instances even finding a feasible solution requires too large computing times for an operational use. For this reason we propose an effective Lagrangian heuristic based on a relaxation of the proposed model and some greedy and exchange algorithms. Computational results on both real and synthetic projects show the effectiveness of the proposed approach. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： mixed integer linear programming Software engineering Agile methods Optimization models Matheuristics Lagrangian heuristics

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Procedure for the Selection among Technologies. Treatment of Deodorizer Distillate Oil

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2014年第43期53卷 16803-16812页

作者： Laoretani, Daniela S. Iribarren, Oscar A. Inst Desarrollo & Diseno INGAR Conicet UTN Santa Fe Argentina

With the aim of both adding value by recovering tocopherols from a natural source and promoting environmental care, this work studies how to select among available technological alternatives for the processing of deodorizer distillate oil (DDO), which is a residue of the edible oils refining industry. The work focuses on how to generate a first set of promising alternatives (we propose to follow an established process design procedure based on heuristics, combined with a screening of the literature, with criteria to narrow the large number of alternatives published). The final selection among them is an established approach: we propose to implement a multiobjective optimization mixed integer linear program maximizing the net present value (NPV) and minimizing the generation of greenhouse gases measured as kilogram-equivalent of CO2. For a given case study of soybean DDO the first step generated a set of six technologies for the treatment of DDO with different processing capacities plus two additional alternatives for the final destination of DDO. The Pareto set of solutions constructed with the results provides information to adopt a both economic and environmentally sound choice of a processing technology. For the particular case analyzed, the technology that maximizes NPV within the Pareto set of solutions was esterification of free fatty acids with ethanol in acid medium followed by a separation of the esters by molecular distillation, at the largest production capacity (576,000 kg/year). This technology gives the maximum NPV of $19,574,000 generating 5,142,500 kg of CO2-equiv. The results obtained are useful for decision making in the industry, to give an adequate final destination to the residue DDO.

关键词： VITAMIN E DEODORIZATION ENVIRONMENTAL health EDIBLE fats & oils mixed integer linear programming NET present value

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