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FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2013年第3期25卷 343-366页

作者： Wang, I-Lin Wang, Yi-Chi Chen, Chih-Wei Natl Cheng Kung Univ Dept Ind & Informat Management Tainan 701 Taiwan Feng Chia Univ Dept Ind Engn & Syst Management Taichung 40724 Taiwan

We investigate a difficult scheduling problem in a semiconductor manufacturing process that seeks to minimize the number of tardy jobs and makespan with sequence-dependent setup time, release time, due dates and tool constraints. We propose a mixed integer programming (MIP) formulation which treats tardy jobs as soft constraints so that our objective seeks the minimum weighted sum of makespan and heavily penalized tardy jobs. Although our polynomial-sized MIP formulation can correctly model this scheduling problem, it is so difficult that even a feasible solution can not be calculated efficiently for small-scale problems. We then propose a technique to estimate the upper bound for the number of jobs processed by a machine, and use it to effectively reduce the size of the MIP formulation. In order to handle real-world large-scale scheduling problems, we propose an efficient dispatching rule that assigns a job of the earliest due date to a machine with least recipe changeover (EDDLC) and try to re-optimize the solution by local search heuristics which involves interchange, translocation and transposition between assigned jobs. Our computational experiments indicate that EDDLC and our proposed reoptimization techniques are very efficient and effective. In particular, our method usually gives solutions very close to the exact optimum for smaller scheduling problems, and calculates good solutions for scheduling up to 200 jobs on 40 machines within 10 min.

关键词： Scheduling mixed integer programming Dispatching rule Local search

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Discovery and analysis of consistent active subnetworks in cancers

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BMC BIOINFORMATICS 2013年第2-sup期14卷 1-11页

作者： Gaire, Raj K. Smith, Lorey Humbert, Patrick Bailey, James Stuckey, Peter J. Haviv, Izhak Univ Melbourne NICTA Victoria Lab Parkville Vic 3010 Australia Univ Melbourne Dept Comp & Informat Syst Parkville Vic 3010 Australia Baker IDI Heart & Diabet Inst Melbourne Vic 3004 Australia Peter MacCallum Canc Ctr Melbourne Vic 3002 Australia Univ Melbourne Sch Med Dept Pathol Melbourne Vic 3010 Australia Bar Ilan Univ Fac Med Galilee IL-52100 Ramat Gan Israel

Gene expression profiles can show significant changes when genetically diseased cells are compared with non-diseased cells. Biological networks are often used to identify active subnetworks (ASNs) of the diseases from the expression profiles to understand the reason behind the observed changes. Current methodologies for discovering ASNs mostly use undirected PPI networks and node centric approaches. This can limit their ability to find the meaningful ASNs when using integrated networks having comprehensive information than the traditional protein-protein interaction networks. Using appropriate scoring functions to assess both genes and their interactions may allow the discovery of better ASNs. In this paper, we present CASNet, which aims to identify better ASNs using (i) integrated interaction networks (mixed graphs), (ii) directions of regulations of genes, and (iii) combined node and edge scores. We simplify and extend previous methodologies to incorporate edge evaluations and lessen their sensitivity to significance thresholds. We formulate our objective functions using mixed integer programming (MIP) and show that optimal solutions may be obtained. We compare the ASNs obtained by CASNet and similar other approaches to show that CASNet can often discover more meaningful and stable regulatory ASNs. Our analysis of a breast cancer dataset finds that the positive feedback loops across 7 genes, AR, ESR1, MYC, E2F2, PGR, BCL2 and CCND1 are conserved across the basal/triple negative subtypes in multiple datasets that could potentially explain the aggressive nature of this cancer subtype. Furthermore, comparison of the basal subtype of breast cancer and the mesenchymal subtype of glioblastoma ASNs shows that an ASN in the vicinity of IL6 is conserved across the two subtypes. This result suggests that subtypes of different cancers can show molecular similarities indicating that the therapeutic approaches in different types of cancers may be shared.

关键词： Interaction Network mixed integer programming Differentially Express Gene Intrinsic Subtype Breast Cancer Dataset

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SOLVING mixed integer BILINEAR PROBLEMS USING MILP FORMULATIONS

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SIAM JOURNAL ON OPTIMIZATION 2013年第2期23卷 721-744页

作者： Gupte, Akshay Ahmed, Shabbir Cheon, Myun Seok Dey, Santanu Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA ExxonMobil Res & Engn Co Annandale NJ 08801 USA

In this paper, we examine a mixed integer linear programming reformulation for mixed integer bilinear problems where each bilinearterm involves the product of a nonnegative integer variable and a nonnegative continuous variable. This reformulation is obtained by first replacing a general integer variable with its binary expansion and then using McCormick envelopes to linearize the resulting product of continuous and binary variables. We present the convex hull of the underlying mixed integer linear set. The effectiveness of this reformulation and associated facet-defining inequalities are computationally evaluated on five classes of instances.

关键词： bilinear problems McCormick envelopes binary expansion cutting planes mixed integer programming

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An integer programming Formulation of the Parsimonious Loss of Heterozygosity Problem

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2013年第6期10卷 1391-1402页

作者： Catanzaro, Daniele Labbe, Martine Halldorsson, Bjarni V. Univ Libre Bruxelles Dept Comp Sci Graphs & Math Optimizat Unit B-1050 Brussels Belgium Reykjavk Univ Sch Sci & Engn Dept Biomed Engn IS-101 Reykjavik Iceland

A loss of heterozygosity (LOH) event occurs when, by the laws of Mendelian inheritance, an individual should be heterozygote at a given site but, due to a deletion polymorphism, is not. Deletions play an important role in human disease and their detection could provide fundamental insights for the development of new diagnostics and treatments. In this paper, we investigate the parsimonious loss of heterozygosity problem (PLOHP), i.e., the problem of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas. Specifically, we generalize Halldorsson et al.'s work by providing a more general formulation of the PLOHP and by showing how one can incorporate different recombination rates and prior knowledge about the locations of deletions. Moreover, we show that the PLOHP can be formulated as a specific version of the clique partition problem in a particular class of graphs called undirected catch-point interval graphs and we prove its general NP-hardness. Finally, we provide a state-of-the-art integer programming (IP) formulation and strengthening valid inequalities to exactly solve real instances of the PLOHP containing up to 9,000 individuals and 3,000 SNPs. Our results give perspectives on the mathematics of the PLOHP and suggest new directions on the development of future efficient exact solution approaches.

关键词： Clique partitioning submodular functions polymatroid rank functions undirected catch-point interval graph combinatorial optimization mixed integer programming computational biology loss of heterozygosity genome-wide association studies single nucleotide polymorphism

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SAMPLING DECISIONS IN OPTIMUM EXPERIMENTAL DESIGN IN THE LIGHT OF PONTRYAGIN'S MAXIMUM PRINCIPLE

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 2013年第4期51卷 3181-3207页

作者： Sager, Sebastian Univ Magdeburg D-39106 Magdeburg Germany

Optimum experimental design (OED) problems are optimization problems in which an experimental setting and decisions on when to measure-the so-called sampling design-are to be determined such that a follow-up parameter estimation yields accurate results for model parameters. In this paper we use the interpretation of OED as optimal control problems with a very particular structure for the analysis of optimal sampling decisions. We introduce the information gain function, motivated by an analysis of necessary conditions of optimality. We highlight differences between problem formulations and propose to use a linear penalization of sampling decisions to overcome the intrinsic ill-conditioning of OED. The results of this paper are independent from the actual numerical method to compute the solution to the OED problem and of the question of local and global optima.

关键词： optimal design of experiments optimal control mixed integer programming

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mixed model disassembly line balancing problem with fuzzy goals

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第20期51卷 6082-6096页

作者： Paksoy, Turan Gungor, Askiner Ozceylan, Eren Hancilar, Arif Selcuk Univ Dept Ind Engn Konya Turkey Pamukkale Univ Dept Ind Engn Denizli Turkey

The collection of used products is the driving force of remanufacturing systems and enterprises can gain significant economic, technical and social benefits from recycling. All products are disassembled up to some level in remanufacturing systems. The best way to disassemble returned products is valid by a well-balanced disassembly line. In this paper, a mixed integer programming (MIP) model is proposed for a mixed model disassembly line balancing (MMDLB) problem with multiple conflicting objectives: (1) minimising the cycle time, (2) minimising the number of disassembly workstations and (3) providing balanced workload per workstation. In most real world MMDLB problems, the targeted goals of decision makers are frequently imprecise or fuzzy because some information may be incomplete and/or unavailable over the planning horizon. This study is the first in the literature to offer the binary fuzzy goal programming (BFGP) and the fuzzy multi-objective programming (FMOP) approaches for the MMDLB problem in order to take into account the vague aspirations of decision makers. An illustrative example based on two industrial products is presented to demonstrate the validity of the proposed models and to compare the performances of the BFGP and the FMOP approaches.

关键词： disassembly disassembly line balancing mixed model disassembly lines binary fuzzy goal programming fuzzy multi-objective programming mixed integer programming

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A hybrid VNS approach for the short-term production planning and scheduling: A case study in the pulp and paper industry

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COMPUTERS & OPERATIONS RESEARCH 2013年第7期40卷 1804-1818页

作者： Figueira, Goncalo Santos, Maristela Oliveira Almada-Lobo, Bernardo Univ Porto INESC TEC Fac Engn P-4200465 Oporto Portugal Univ Sao Paulo Inst Ciencias Matemat & Comp BR-13560970 Sao Carlos SP Brazil

Mathematical formulations for production planning are increasing complexity, in order to improve their realism. In short-term planning, the desirable level of detail is particularly high. Exact solvers fail to generate good quality solutions for those complex models on medium- and large-sized instances within feasible time. Motivated by a real-world case study in the pulp and paper industry, this paper provides an efficient solution method to tackle the short-term production planning and scheduling in an integrated mill. Decisions on the paper machine setup pattern and on the production rate of the pulp digester (which is constrained to a maximum variation) complicate the problem. The approach is built on top of a mixed integer programming (MIP) formulation derived from the multi-stage general lotsizing and scheduling problem. It combines a Variable Neighbourhood Search procedure which manages the setup-related variables, a specific heuristic to determine the digester's production speeds and an exact method to optimize the production and flow movement decisions. Different strategies are explored to speed-up the solution procedure and alternative variants of the algorithm are tested on instances based on real data from the case study. The algorithm is benchmarked against exact procedures. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Multi-stage lotsizing and scheduling Production rates Pulp and paper industry mixed integer programming Variable Neighbourhood Search Hybrid methods

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Market-driven operational optimization of industrial gas supply chains

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COMPUTERS & CHEMICAL ENGINEERING 2013年 56卷 128-141页

作者： Manenti, Flavio Rovaglio, Maurizio Politecn Milan Dipartimento Chim Mat & Ingn Chim Giulio Natta I-20133 Milan Italy Invensys Operat Management Lake Forest CA 92630 USA

This paper deals with the operational optimization of industrial gas supply chains. Industrial gas networks differ from other applications and require a rather special and shrewd approach to modeling and optimization issues. Currently in industrial gas plants: (i) the raw material is free;(ii) binding contracts and clauses place tight limits on supplies, production and distribution;(iii) electric energy cost fluctuations wield a greater influence over overall production than in other industrial areas;(iv) market demand is subject to multifaceted fluctuations and uncertainties;(v) long-term market demand is usually regulated by take-or-pay contracts;(vi) main users are on-site or connected via pipeline;and (vii) cryogenic storage constitutes a significant expense and encourages companies to veer toward just-in-time production. This paper also provides very general guidelines for dealing with the aforementioned peculiarities, and compares plant-wide and enterprise-wide optimizations of industrial gas networks. An existing network is adopted as industrial case study. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Industrial gases Supply chain mixed integer programming Plant-wide optimization Enterprise-wide optimization Operational planning

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The burn-in test scheduling problem with batch dependent processing time and sequence dependent setup time

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第6期51卷 1694-1706页

作者： Pearn, W. L. Hong, J. S. Tai, Y. T. Natl Chiao Tung Univ Dept Ind Engn & Management Hsinchu Taiwan Kainan Univ Dept Informat Management Tao Yuan Taiwan

The burn-in test scheduling problem (BTSP) is a variation of the complex batch processing machine scheduling problem, which is also a generalisation of the liquid crystal injection scheduling problem with incompatible product families and classical identical parallel machine problem. In the case we investigated on the BTSP, the jobs are clustered by their product families. The product families can be clustered by different product groups. In the same product group, jobs with different product families can be processed as a batch. The batch processing time is dependent on the longest processing time of those jobs in that batch. Setup times between two consecutive batches of different product groups on the same batch machine are sequentially dependent. In addition, the unequal ready times are considered in the BTSP which involves the decisions of batch formation and batch scheduling in order to minimise the total machine workload without violating due dates and the limited machine capacity restrictions. Since the BTSP involves constraints on unequal ready time, batch dependent processing time, and sequence dependent setup times, it is more difficult to solve than the classical parallel batch processing machine scheduling problem with compatible product families or incompatible product families. These restrictions mean that the existing methods cannot be applied into real-world factories directly. Consequently, this paper proposes a mixed integer programming model to solve the BTSP exactly. In addition, two efficient solution procedures which solve the BTSP are also presented.

关键词： batch incompatible product family mixed integer programming burn-in test

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Analysis of Energy Efficiency of Compressive Sensing in Wireless Sensor Networks

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IEEE SENSORS JOURNAL 2013年第5期13卷 1999-2008页

作者： Karakus, Celalettin Gurbuz, Ali Cafer Tavli, Bulent TOBB Univ Econ & Technol TR-06560 Ankara Turkey

Improving the lifetime of wireless sensor networks (WSNs) is directly related to the energy efficiency of computation and communication operations in the sensor nodes. Compressive sensing (CS) theory suggests a new way of sensing the signal with a much lower number of linear measurements as compared to the conventional case provided that the underlying signal is sparse. This result has implications on WSN energy efficiency and prolonging network lifetime. In this paper, the effects of acquiring, processing, and communicating CS-based measurements on WSN lifetime are analyzed in comparison to conventional approaches. Energy dissipation models for both CS and conventional approaches are built and used to construct a mixed integer programming framework that jointly captures the energy costs for computation and communication for both CS and conventional approaches. Numerical analysis is performed by systematically sampling the parameter space (i.e., sparsity levels, network radius, and number of nodes). Our results show that CS prolongs network lifetime for sparse signals and is more advantageous for WSNs with a smaller coverage area.

关键词： Compressive sensing (CS) energy efficiency mixed integer programming network lifetime wireless sensor networks (WSN)

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