Optimizing a Pipeline Operation by Constraint Logic Programming (CLP) and Mixed Integer Linear Programming (MILP)

2004 ◽  
Author(s):  
L. Magata˜o ◽  
L. V. R. Arruda ◽  
F. Neves
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Logic Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Constraint Logic Programming ◽  
Mixed Integer ◽  
Pipeline System ◽  
Liquefied Petroleum Gas ◽  
Milp Model

This paper addresses the problem of developing an optimization structure to aid the operational decision-making in a real-world pipeline scenario. The pipeline connects an inland refinery to a harbor, conveying different types of products (gasoline, diesel, kerosene, alcohol, liquefied petroleum gas, jet fuel, etc). The scheduling of activities has to be specified in advance by a specialist, who must provide low cost operational procedures. The specialist has to take into account issues concerning product availability, tankage constraints, pumping sequencing, flow rate determination, and a series of operational requirements. Thus, the decision-making process is hard and error-prone due to the diversity of aspects to be considered. Nevertheless, the developed optimization structure can aid the specialist in solving the pipeline scheduling task with improved efficiency. Such optimization structure has its core in a novel mathematical approach, which uses Constraint Logic Programming (CLP) and Mixed Integer Linear Programming (MILP) technologies in an integrated CLP-MILP model. In particular, the integration of CLP and MILP technologies has been recognized as an emerging discipline for achieving the best that CLP and MILP can contribute to solve scheduling problems [1]. The scheme used for integrating CLP and MILP is double modeling [1], and the combined CLP-MILP model is implemented and solved by using a commercial tool [2]. Illustrative instances demonstrate that the optimization structure is able to define new operational points to the pipeline system, providing significant cost saving.

scholarly journals Um modelo híbrido (CLP-MILP) para scheduling de operações em polidutos

2008 ◽  
Vol 28 (3) ◽  
pp. 511-543 ◽  
Author(s):  
Leandro Magatão ◽  
Lúcia Valéria Ramos de Arruda ◽  
Flávio Neves-Jr
Keyword(s):  
Linear Programming ◽  
Logic Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Constraint Logic Programming ◽  
Mixed Integer

A eficácia na transferência de derivados de petróleo através de dutos motiva a execução deste trabalho. O objetivo principal é a modelagem do scheduling de um poliduto, isto é, um sistema de dutos que transporta diferentes derivados de petróleo. O poliduto em estudo com 93,5 km de extensão conecta uma refinaria a um terminal portuário. Foi desenvolvido um modelo de otimização baseado na união de Constraint Logic Programming (CLP) e Mixed Integer Linear Programming (MILP). O modelo utiliza uma abordagem de decomposição do problema, com representação temporal contínua e calcula janelas de tempo (restrições temporais) que devem ser respeitadas. A abordagem híbrida CLP-MILP proporcionou a solução de cenários reais em tempo computacional da ordem de segundos. A resolução computacional do modelo proposto evidenciou novos pontos de operação para o poliduto, proporcionando ganhos operacionais significativos. O modelo implementado configura uma ferramenta de auxílio para tomada de decisões operacionais no cenário estudado.

scholarly journals Optimising the selection of food items for FFQs using Mixed Integer Linear Programming

2014 ◽  
Vol 18 (1) ◽  
pp. 68-74 ◽  
Author(s):  
Johanna C Gerdessen ◽  
Olga W Souverein ◽  
Pieter van ‘t Veer ◽  
Jeanne HM de Vries
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Selection Process ◽  
Saturated Fat ◽  
Mixed Integer ◽  
Monounsaturated Fat ◽  
Food Items ◽  
Milp Model ◽  
Selection Of

AbstractObjectiveTo support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible.DesignSelection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium.ResultsThe food lists generated by the MILP model have good performance in terms of length, coverage and R2 (explained variance) of all nutrients. MILP-generated food lists were 32–40 % shorter than a benchmark food list, whereas their quality in terms of R2 was similar to that of the benchmark.ConclusionsThe results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.

scholarly journals Spillways Scheduling for Flood Control of Three Gorges Reservoir Using Mixed Integer Linear Programming Model

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Maoyuan Feng ◽  
Pan Liu
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Three Gorges Reservoir ◽  
Flood Control ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Three Gorges ◽  
Reservoir Storage ◽  
Milp Model

This study proposes a mixed integer linear programming (MILP) model to optimize the spillways scheduling for reservoir flood control. Unlike the conventional reservoir operation model, the proposed MILP model specifies the spillways status (including the number of spillways to be open and the degree of the spillway opened) instead of reservoir release, since the release is actually controlled by using the spillway. The piecewise linear approximation is used to formulate the relationship between the reservoir storage and water release for a spillway, which should be open/closed with a status depicted by a binary variable. The control order and symmetry rules of spillways are described and incorporated into the constraints for meeting the practical demand. Thus, a MILP model is set up to minimize the maximum reservoir storage. The General Algebraic Modeling System (GAMS) and IBM ILOG CPLEX Optimization Studio (CPLEX) software are used to find the optimal solution for the proposed MILP model. The China’s Three Gorges Reservoir, whose spillways are of five types with the total number of 80, is selected as the case study. It is shown that the proposed model decreases the flood risk compared with the conventional operation and makes the operation more practical by specifying the spillways status directly.

scholarly journals Mixed-Integer Linear Programming Model by Linear Approximation for a Strike Package-to-Target Assignment Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Heungseob Kim
Keyword(s):  
Linear Programming ◽  
Linear Approximation ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Heterogeneous Vehicle Routing Problem ◽  
Target Assignment ◽  
Milp Model

This study deals with an aircraft-to-target assignment (ATA) problem considering the modern air operation environment, such as the strike package concept, multiple targets for a sortie, and the strike packages’ survivability. For the ATA problem, this study introduces a novel mathematical model in which a heterogeneous vehicle routing problem (HVRP) and a weapon-to-target assignment (WTA) problem are conceptually integrated. The HVRP generates the flight routes for strike packages because this study confirms that the survivability of a strike package depends on the path, and the WTA problem evaluates the likelihood of successful target destruction of assigned weapons. Although the first version of the model is developed as a mixed-integer nonlinear programming (MINLP) model, this study attempts to convert it to a mixed-integer linear programming (MILP) model using the logarithmic transformation and piecewise linear approximation methods. For an ATA problem, this activity could provide an opportunity to use the excellent existing algorithms for searching the optimal solution of LP models. To maximize the operational effectiveness, the MILP model simultaneously determines the following for each strike package: (a) composition type, (b) targets, (c) flight route, (d) types, and (e) quantity of weapons for each target.

Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzyTOPSIS

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Umar Muhammad Modibbo ◽  
Musa Hassan ◽  
Aquil Ahmed ◽  
Irfan Ali
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Pharmaceutical Company ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Supplier Selection ◽  
Mixed Integer ◽  
Pharmaceutical Companies ◽  
Content Type

PurposeSupplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.Design/methodology/approachThe concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.FindingsThis study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.Research limitations/implicationsThis research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.Practical implicationsThis work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.Originality/valueIn this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

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