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Linear Programming (linear + programming)
Kinds of Linear Programming Terms modified by Linear Programming Selected AbstractsLinear Programming and the von Neumann ModelMETROECONOMICA, Issue 1 2000Christian Bidard The formal similarity between von Neumann's theorem on maximal growth and (a weak form of) the fundamental theorem of linear programming is striking. The parallelism is explained by considering a simple economy for which the two problems are identical. [source] Shortest path stochastic control for hybrid electric vehiclesINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 14 2008Edward Dean Tate Jr Abstract When a hybrid electric vehicle (HEV) is certified for emissions and fuel economy, its power management system must be charge sustaining over the drive cycle, meaning that the battery state of charge (SOC) must be at least as high at the end of the test as it was at the beginning of the test. During the test cycle, the power management system is free to vary the battery SOC so as to minimize a weighted combination of fuel consumption and exhaust emissions. This paper argues that shortest path stochastic dynamic programming (SP-SDP) offers a more natural formulation of the optimal control problem associated with the design of the power management system because it allows deviations of battery SOC from a desired setpoint to be penalized only at key off. This method is illustrated on a parallel hybrid electric truck model that had previously been analyzed using infinite-horizon stochastic dynamic programming with discounted future cost. Both formulations of the optimization problem yield a time-invariant causal state-feedback controller that can be directly implemented on the vehicle. The advantages of the shortest path formulation include that a single tuning parameter is needed to trade off fuel economy and emissions versus battery SOC deviation, as compared with two parameters in the discounted, infinite-horizon case, and for the same level of complexity as a discounted future-cost controller, the shortest-path controller demonstrates better fuel and emission minimization while also achieving better SOC control when the vehicle is turned off. Linear programming is used to solve both stochastic dynamic programs. Copyright © 2007 John Wiley & Sons, Ltd. [source] OPTIMIZATION OF WHEAT BLENDING TO PRODUCE BREADMAKING FLOURJOURNAL OF FOOD PROCESS ENGINEERING, Issue 3 2001MEHMET HAYTA ABSTRACT Linear programming was utilized to optimize the blending of wheat lots which have different quality characteristic and costs. Using best subsets regression three quality tests (particle size index, dough volume and falling number value) were selected in relation to loaf volume of bread to be produced. The chosen criteria were set up in a linear programming format as a model for the computerized solution. The model's applicability was assessed in a commercial mill. As a result of applying the model it was found possible to produce breadmaking flour with a reasonable quality and at a lower cost. [source] Coordinated Capacitated Lot-Sizing Problem with Dynamic Demand: A Lagrangian HeuristicDECISION SCIENCES, Issue 1 2004E. Powell Robinson Jr. ABSTRACT Coordinated replenishment problems are common in manufacturing and distribution when a family of items shares a common production line, supplier, or a mode of transportation. In these situations the coordination of shared, and often limited, resources across items is economically attractive. This paper describes a mixed-integer programming formulation and Lagrangian relaxation solution procedure for the single-family coordinated capacitated lot-sizing problem with dynamic demand. The problem extends both the multi-item capacitated dynamic demand lot-sizing problem and the uncapacitated coordinated dynamic demand lot-sizing problem. We provide the results of computational experiments investigating the mathematical properties of the formulation and the performance of the Lagrangian procedures. The results indicate the superiority of the dual-based heuristic over linear programming-based approaches to the problem. The quality of the Lagrangian heuristic solution improved in most instances with increases in problem size. Heuristic solutions averaged 2.52% above optimal. The procedures were applied to an industry test problem yielding a 22.5% reduction in total costs. [source] An agent-based scheduling method enabling rescheduling with trial-and-error approachELECTRICAL ENGINEERING IN JAPAN, Issue 1 2007Hiroyasu Mitsui Abstract Scheduling optimization is an extremely difficult problem; therefore, many scheduling methods such as linear programming or stochastic searching have been investigated in order to obtain better solutions close to the optimum one. After obtaining a certain solution, scheduling managers may need to reschedule another solution that corresponds to changes in requirements or resources. However, rescheduling problems become more difficult as they become larger in scale. In this paper, we propose an agent-based rescheduling system using the linear programming approach. In our system, agents can autonomously conduct rescheduling on behalf of managers by repeated trial and error in balancing loads or changing the priority of resource allocation until it reaches a better solution for the requirement is obtained. In addition, managers can engage in trial and error with the help of agents to seek a better solution by changing constraint conditions. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(1): 26,38, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20434 [source] Transmission network expansion planning with security constraints based on bi-level linear programmingEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2009Hong Fan Abstract In deregulated power market, multiple conflicting objectives with many constraints should be balanced in transmission planning. The primary objective is to ensure the reliable supply to the demand as economically as possible. In this paper, a new bi-level linear programming model for transmission network expansion planning (TNEP) with security constraints has been proposed. The modeling improves traditional building style by adding reliability planning into economy planning as constraints, letting optimal planning strategy be more economic and highly reliable. A hybrid algorithm which integrates improved niching genetic algorithm and prime-dual interior point method is newly proposed to solve the TNEP based on bi-level programming. The advantages of the new methodology include (1) the highest reliability planning scheme can be acquired as economically as possible; (2) new model avoids the contradictions of conflicting objectives in TNEP, and explores new ideas for TNEP modeling; (3) the proposed hybrid algorithm is able to solve bi-level programming and fully manifests the merits of two algorithms as well. Simulation results obtained from two well-known systems and comparison analysis reveal that the proposed methodology is valid. Copyright © 2008 John Wiley & Sons, Ltd. [source] An efficient methodology for security assessment of power systems based on distributed optimal power flowEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2003D. Hur This paper presents an algorithm for the parallel solution of the security constrained optimal power flow (SCOPF) problem in a decentralized framework, consisting of regions, using a price-based mechanism that models each region as an economic unit. We first solve the distributed optimal power flow (OPF) problem to determine the maximum secure simultaneous transfer capability of each tie-line between adjacent regions by taking only the security constraints imposed on the tie-lines into account. In this paper, the line outage distribution factors (LODF) calculated at the current state are used to formulate the appended constraints. Once the secure transfer capability of each tie-line is determined, the intra-regional SCOPF is performed using the conventional linear programming (LP) approach. A description on the inclusion of security constraints with distributed OPF algorithm will be given, followed by the case study for Korea Electric Power System. [source] Linear-programming-based method for optimum schedule of reactive power sources in integrated AC-DC power systemsEUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 1 2003M. Abdel-Salam This paper is aimed at obtaining the optimal flow of reactive power which corresponds to minimum real power losses in integrated AC-DC power systems including one DC link. The DC power or DC current, drawn by the link at its rectifier side is introduced as a new control variable added to the normal control variables, i.e. transformer tap-settings, generator terminal voltages and reactive-power outputs, and switchable reactive power sources. The constraints include the reactive power limits of the generators, limits on the load bus voltages and the operating limits of the control variables. Dual linear programming is applied to minimize an objective function for system losses. Application of the proposed method on different test AC-DC systems confirmed that less system losses is achieved with the introduction of the DC control variable. [source] Inducing safer oblique trees without costsEXPERT SYSTEMS, Issue 4 2005Sunil Vadera Abstract: Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming. [source] Bearing capacity of two interfering footingsINTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 3 2008Jyant Kumar Abstract By using an upper bound limit analysis in conjunction with finite elements and linear programming, the ultimate bearing capacity of two interfering rough strip footings, resting on a cohesionless medium, was computed. Along all the interfaces of the chosen triangular elements, velocity discontinuities were employed. The plastic strains were incorporated using an associated flow rule. For different clear spacing (S) between the two footings, the efficiency factor (,,) was determined, where ,, is defined as the ratio of the failure load for a strip footing of given width in the presence of the other footing to that of a single isolated strip footing having the same width. The value of ,, at S/B = 0 becomes equal to 2.0, and the maximum ,, occurs at S/B = ,Scr/B. For S/B,Scr/B, the ultimate failure load for a footing becomes almost half that of an isolated footing having width (2B + S), and the soil mass below and in between the two footings deforms mainly in the downward direction. In contrast, for S/B>Scr/B, ground heave was noticed along both the sides of the footing. As compared to the available theories, the analysis provides generally lower values of ,, for S/B>Scr/B. Copyright © 2007 John Wiley & Sons, Ltd. [source] Rigid-plastic/rigid-viscoplastic FE simulation using linear programming for metal formingINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 4 2003Weili Xu Abstract For rigid-plastic/rigid-viscoplastic (RP/RVP) FE simulation in metal forming processes, the linear programming (LP) approach has many remarkable advantages, compared with a normal iterative solver. This approach is free from convergence problems and is convenient for dealing with contact surfaces, rigid zones, and friction forces. In this paper, a numerical model for axisymmetrical and plane-strain analysis using RP/RVP and LP is proposed and applied to industrial metal forming. Numerical examples are provided to validate the accuracy and efficiency of the proposed method. Copyright © 2002 John Wiley & Sons, Ltd. [source] A general non-linear optimization algorithm for lower bound limit analysisINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 2 2003Kristian Krabbenhoft Abstract The non-linear programming problem associated with the discrete lower bound limit analysis problem is treated by means of an algorithm where the need to linearize the yield criteria is avoided. The algorithm is an interior point method and is completely general in the sense that no particular finite element discretization or yield criterion is required. As with interior point methods for linear programming the number of iterations is affected only little by the problem size. Some practical implementation issues are discussed with reference to the special structure of the common lower bound load optimization problem, and finally the efficiency and accuracy of the method is demonstrated by means of examples of plate and slab structures obeying different non-linear yield criteria. Copyright © 2002 John Wiley & Sons, Ltd. [source] Modeling an industrial energy system: Perspectives on regional heat cooperationINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 9 2008S. Klugman Abstract Through energy efficiency measures, it is possible to reduce heat surplus in the pulp and paper industry. Yet pulp and paper mills situated in countries with a heat demand for residential and commercial buildings for the major part of the year are potential heat suppliers. However, striving to utilize the heat within the mills for efficient energy use could conflict with the delivery of excess heat to a district heating system. As part of a project to optimize a regional energy system, a sulfate pulp mill situated in central Sweden is analyzed, focusing on providing heat and electricity to the mill and its surrounding energy systems. An energy system optimization method based on mixed integer linear programming is used for studying energy system measures on an aggregated level. An extended system, where the mill is integrated in a regional heat market (HM), is evaluated in parallel with the present system. The use of either hot sewage or a heat pump for heat deliveries is analyzed along with process integration measures. The benefits of adding a condensing unit to the back-pressure steam turbine are also investigated. The results show that the use of hot sewage or a heat pump for heat deliveries is beneficial only in combination with extended heat deliveries to an HM. Process integration measures are beneficial and even increase the benefit of selling more heat for district heating. Adding a condensing turbine unit is most beneficial in combination with extended heat deliveries and process integration. Copyright © 2007 John Wiley & Sons, Ltd. [source] A personal perspective on problem solving by general purpose solversINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 3 2010Toshihide Ibaraki Abstract To solve the problems that abound in real-world applications, we are proposing an approach of using general-purpose solvers, as we cannot afford to develop special-purpose algorithms for all individual problems. The existing general-purpose solvers such as linear programming and integer programming are very useful but not sufficient. To improve the situation, we have developed solvers for other standard problems such as the constraint satisfaction problem and the resource-constrained project scheduling problem among others. In this article, we describe why general-purpose solvers are needed, what kinds of solvers we considered, how they were developed and where they have been applied. [source] Growth and survival of river catfish Mystus nemurus (Cuvier & Valenciennes) larvae fed isocaloric diets with different protein levels during weaningJOURNAL OF APPLIED ICHTHYOLOGY, Issue 3 2000R. V. Eguia Summary The growth of river catfish Mystus nemurus (Cuvier & Valenciennes) larvae fed four isocaloric diets (4200 kcal kg,1) with different protein levels during weaning was determined. Diets containing 45, 50, 55, and 60% protein were formulated by linear programming using amino acid profiles based on that of 2-day-old river catfish larvae. Artificial diets were fed to the larvae beginning at day 5 after being initially fed Artemia nauplii for 4 days. The larvae thrived solely on artificial diets from day 8 to day 16. On the other hand, the control larvae were fed Artemia nauplii from day 1 to day 16. Results of the feeding trial showed that growth and survival of M. nemurus larvae given the diet containing 60% protein were high and comparable to those of the larvae given only live food (control). Larvae fed the 55% protein diet had significantly lower growth and survival than the larvae on the control and 60% diets but significantly higher growth and survival rates than did larvae fed with 45 and 50% protein diets. Carcass moisture and total lipids after 16 days of feeding did not differ significantly (P > 0.05), but body protein increased with increasing dietary protein. Body protein of the control larvae was similar to that of larvae given the 60% protein diet. [source] Robust identification of piecewise/switching autoregressive exogenous processAICHE JOURNAL, Issue 7 2010Xing Jin Abstract A robust identification approach for a class of switching processes named PWARX (piecewise autoregressive exogenous) processes is developed in this article. It is proposed that the identification problem can be formulated and solved within the EM (expectation-maximization) algorithm framework. However, unlike the regular EM algorithm in which the objective function of the maximization step is built upon the assumption that the noise comes from a single distribution, contaminated Gaussian distribution is utilized in the process of constructing the objective function, which effectively makes the revised EM algorithm robust to the latent outliers. Issues associated with the EM algorithm in the PWARX system identification such as sensitivity to its starting point as well as inability to accurately classify "un-decidable" data points are examined and a solution strategy is proposed. Data sets with/without outliers are both considered and the performance is compared between the robust EM algorithm and regular EM algorithm in terms of their parameter estimation performance. Finally, a modified version of MRLP (multi-category robust linear programming) region partition method is proposed by assigning different weights to different data points. In this way, negative influence caused by outliers could be minimized in region partitioning of PWARX systems. Simulation as well as application on a pilot-scale switched process control system are used to verify the efficiency of the proposed identification algorithm. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] A novel approach to scheduling multipurpose batch plants using unit-slotsAICHE JOURNAL, Issue 7 2010Naresh Susarla Abstract Several models for scheduling multipurpose batch plants exist in the literature. The models using unit-specific event points have shown better solution efficiency on various literature examples. This article presents a novel approach to scheduling multipurpose batch plants, which uses unit-slots instead of process-slots to manage shared resources such as material storage. We develop two slightly different models that are even more compact and simpler than that of Sundaramoorthy and Karimi, Chem Eng Sci. 2005;60:2679,2702. Although we focus on material as a shared resource, our multi-grid approach rationalizes, generalizes, and improves the current multi-grid approaches for scheduling with shared resources. Our models allow nonsimultaneous transfers of materials into and out of a batch. We show by an example that this flexibility can give better schedules than those from existing models in some cases. Furthermore, our approach uses fewer slots (event-points) on some examples than even those required by the most recent unit-specific event-based model. Numerical evaluation using literature examples shows significant gains in solution efficiency from the use of unit-slots except where the number of unit-slots required for the optimal solution equals that of process slots. We also highlight the importance of constraint sequencing in GAMS implementation for evaluating mixed-integer linear programming based scheduling models fairly. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] A bi-criterion optimization approach for the design and planning of hydrogen supply chains for vehicle useAICHE JOURNAL, Issue 3 2010Gonzalo Guillén-Gosálbez Abstract In this article, we address the design of hydrogen supply chains for vehicle use with economic and environmental concerns. Given a set of available technologies to produce, store, and deliver hydrogen, the problem consists of determining the optimal design of the production-distribution network capable of satisfying a predefined hydrogen demand. The design task is formulated as a bi-criterion mixed-integer linear programming (MILP) problem, which simultaneously accounts for the minimization of cost and environmental impact. The environmental impact is measured through the contribution to climate change made by the hydrogen network operation. The emissions considered in the analysis are those associated with the entire life cycle of the process, and are quantified according to the principles of Life Cycle Assessment (LCA). To expedite the search of the Pareto solutions of the problem, we introduce a bi-level algorithm that exploits its specific structure. A case study that addresses the optimal design of the hydrogen infrastructure needed to fulfill the expected hydrogen demand in Great Britain is introduced to illustrate the capabilities of the proposed approach. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] Enhancing molecular discovery using descriptor-free rearrangement clustering techniques for sparse data setsAICHE JOURNAL, Issue 2 2010Peter A. DiMaggio Jr. Abstract This article presents a descriptor-free method for estimating library compounds with desired properties from synthesizing and assaying minimal library space. The method works by identifying the optimal substituent ordering (i.e., the optimal encoding integer assignment to each functional group on every substituent site of molecular scaffold) based on a global pairwise difference metric intended to capture smoothness of the compound library. The reordering can be accomplished via a (i) mixed-integer linear programming (MILP) model, (ii) genetic algorithm based approach, or (iii) heuristic approach. We present performance comparisons between these techniques as well as an independent analysis of characteristics of the MILP model. Two sparsely sampled data matrices provided by Pfizer are analyzed to validate the proposed approach and we show that the rearrangement of these matrices leads to regular property landscapes which enable reliable property estimation/interpolation over the full library space. An iterative strategy for compound synthesis is also introduced that utilizes the results of the reordered data to direct the synthesis toward desirable compounds. We demonstrate in a simulated experiment using held out subsets of the data that the proposed iterative technique is effective in identifying compounds with desired physical properties. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] Multi-component analysis: blind extraction of pure components mass spectra using sparse component analysisJOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 9 2009Ivica Kopriva Abstract The paper presents sparse component analysis (SCA)-based blind decomposition of the mixtures of mass spectra into pure components, wherein the number of mixtures is less than number of pure components. Standard solutions of the related blind source separation (BSS) problem that are published in the open literature require the number of mixtures to be greater than or equal to the unknown number of pure components. Specifically, we have demonstrated experimentally the capability of the SCA to blindly extract five pure components mass spectra from two mixtures only. Two approaches to SCA are tested: the first one based on ,1 norm minimization implemented through linear programming and the second one implemented through multilayer hierarchical alternating least square nonnegative matrix factorization with sparseness constraints imposed on pure components spectra. In contrast to many existing blind decomposition methods no a priori information about the number of pure components is required. It is estimated from the mixtures using robust data clustering algorithm together with pure components concentration matrix. Proposed methodology can be implemented as a part of software packages used for the analysis of mass spectra and identification of chemical compounds. Copyright © 2009 John Wiley & Sons, Ltd. [source] Material handling device selection in cellular manufacturingJOURNAL OF MULTI CRITERIA DECISION ANALYSIS, Issue 6 2001Marcello Braglia Abstract This paper presents a new multi-criteria decision model for the material handling device (MHD) selection problem in cellular manufacturing systems. Given a set of manufacturing cells based on several automatic work-centres, the technique makes it possible to select a particular MHD for each cell in an integrated way, with different constraints being taken into consideration. The approach is based on two different multi-attribute analyses executed with analytic hierarchy process (AHP) methodology, and a final integer linear programming including important limitations faced by the designer when making MHD investment decisions. An example using real data is provided to illustrate this methodology. Copyright © 2002 John Wiley & Sons, Ltd. [source] Relevance of Web documents: Ghosts consensus methodJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 10 2002Andrey L. Gorbunov The dominant method currently used to improve the quality of Internet search systems is often called "digital democracy." Such an approach implies the utilization of the majority opinion of Internet users to determine the most relevant documents: for example, citation index usage for sorting of search results (google.com) or an enrichment of a query with terms that are asked frequently in relation with the query's theme. "Digital democracy" is an effective instrument in many cases, but it has an unavoidable shortcoming, which is a matter of principle: the average intellectual and cultural level of Internet users is very low,everyone knows what kind of information is dominant in Internet query statistics. Therefore, when one searches the Internet by means of "digital democracy" systems, one gets answers that reflect an underlying assumption that the user's mind potential is very low, and that his cultural interests are not demanding. Thus, it is more correct to use the term "digital ochlocracy" to refer to Internet search systems with "digital democracy." Based on the well-known mathematical mechanism of linear programming, we propose a method to solve the indicated problem. [source] Randomized Stopping Times and American Option Pricing with Transaction CostsMATHEMATICAL FINANCE, Issue 1 2001Prasad Chalasani In a general discrete-time market model with proportional transaction costs, we derive new expectation representations of the range of arbitrage-free prices of an arbitrary American option. The upper bound of this range is called the upper hedging price, and is the smallest initial wealth needed to construct a self-financing portfolio whose value dominates the option payoff at all times. A surprising feature of our upper hedging price representation is that it requires the use of randomized stopping times (Baxter and Chacon 1977), just as ordinary stopping times are needed in the absence of transaction costs. We also represent the upper hedging price as the optimum value of a variety of optimization problems. Additionally, we show a two-player game where at Nash equilibrium the value to both players is the upper hedging price, and one of the players must in general choose a mixture of stopping times. We derive similar representations for the lower hedging price as well. Our results make use of strong duality in linear programming. [source] FORMALIZING WIESER's THEORY OF DISTRIBUTION: CONSISTENT IMPUTATION IN ALTERNATIVE THEORETICAL PERSPECTIVESMETROECONOMICA, Issue 2 2005Arrigo OpocherArticle first published online: 18 MAY 200 ABSTRACT Wieser's theory of value and distribution has been formalized and interpreted mainly in the framework of efficient allocation of scarce resources. To this end, the mathematical techniques of linear programming have been used by such authors as Samuelson and Uzawa. This paper presents briefly what may be called the Knight,Samuelson,Uzawa formalization and supplements it with different proposed formalizations of some further aspects consistently developed in Wieser's works. The formalization that we propose concerns Wieser's theory of interest and his theory of value for ,cost goods'. It is argued that in such cases the produced means of production, and not the endowments of scarce resources, are at the centre of Wieser's analysis. It is shown that some appropriately specified models in the Sraffa,von Neumann,Leontief tradition can very usefully be employed in order to strengthen Wieser's intuitive arguments and give them a sound analytical structure. [source] Linear Programming and the von Neumann ModelMETROECONOMICA, Issue 1 2000Christian Bidard The formal similarity between von Neumann's theorem on maximal growth and (a weak form of) the fundamental theorem of linear programming is striking. The parallelism is explained by considering a simple economy for which the two problems are identical. [source] Modeling and analysis of multiobjective lot splitting for N -product M -machine flowshop linesNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 4 2010Yossi Bukchin Abstract Lot splitting is a new approach for improving productivity by dividing production lots into sublots. This approach enables accelerating production flow, reducing lead-time and increasing the utilization of organization resources. Most of the lot splitting models in the literature have addressed a single objective problem, usually the makespan or flowtime objectives. Simultaneous minimization of these two objectives has rarely been addressed in the literature despite of its high relevancy to most industrial environments. This work aims at solving a multiobjective lot splitting problem for multiple products in a flowshop environment. Tight mixed-integer linear programming (MILP) formulations for minimizing the makespan and flowtime are presented. Then, the MinMax solution, which takes both objectives into consideration, is defined and suggested as an alternative objective. By solving the MILP model, it was found that minimizing one objective results in an average loss of about 15% in the other objective. The MinMax solution, on the other hand, results in an average loss of 4.6% from the furthest objective and 2.5% from the closest objective. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010 [source] Quay crane scheduling at container terminals to minimize the maximum relative tardiness of vessel departuresNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 1 2006Jiyin Liu Abstract In this paper, we study the problem of scheduling quay cranes (QCs) at container terminals where incoming vessels have different ready times. The objective is to minimize the maximum relative tardiness of vessel departures. The problem can be formulated as a mixed integer linear programming (MILP) model of large size that is difficult to solve directly. We propose a heuristic decomposition approach to breakdown the problem into two smaller, linked models, the vessel-level and the berth-level models. With the same berth-level model, two heuristic methods are developed using different vessel-level models. Computational experiments show that the proposed approach is effective and efficient. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006 [source] Optimal service rates of a service facility with perishable inventory itemsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 5 2002O. Berman In this paper we optimally control service rates for an inventory system of service facilities with perishable products. We consider a finite capacity system where arrivals are Poisson-distributed, lifetime of items have exponential distribution, and replenishment is instantaneous. We determine the service rates to be employed at each instant of time so that the long-run expected cost rate is minimized for fixed maximum inventory level and capacity. The problem is modelled as a semi-Markov decision problem. We establish the existence of a stationary optimal policy and we solve it by employing linear programming. Several numerical examples which provide insight to the behavior of the system are presented. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 464,482, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10021 [source] Optimal control of a water reservoir with expected value,variance criteriaOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 1 2007Andrzej Karbowski Abstract The article presents how to solve a reservoir management problem, which has been formulated as a two-criteria stochastic optimal control problem. Apart from the expected value of a performance index, its variance is also considered. Three approaches are described: a method based on the Lagrange function; a method based on the ordinary moment of the second order (finite time horizon); and a method based on linear programming (infinite time horizon). In the second part of the article, they are assessed in a case study concerning a reservoir in the southern part of Poland. Copyright © 2006 John Wiley & Sons, Ltd. [source] On,off minimum-time control with limited fuel usage: near global optima via linear programmingOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 3 2006Brian J. Driessen Abstract A method for finding a global optimum to the on,off minimum-time control problem with limited fuel usage is presented. Each control can take on only three possible values: maximum, zero, or minimum. The simplex method for linear systems naturally yields nearly such a solution for the re-formulation presented herein because the simplex method always produces an extreme point solution to the linear program. Numerical examples for the benchmark linear flexible system are presented. Copyright © 2006 John Wiley & Sons, Ltd. [source] | |||||||||||||||||||||||||||||||||||||