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A systematic review of mathematical programming models and solution approaches for the textile supply chain

COMPUTERS & INDUSTRIAL ENGINEERING 2025年 202卷

作者： Alves, Giovanna Abreu Tavares, Roberto Amorim, Pedro Camargo, Victor Claudio Bento Univ Fed Sao Carlos Ind Engn Dept Washington Luis Rdkm 235 Sao Carlos SP Brazil Insper Inst Res & Educ R Quata 300 Vila Olimpia SP Brazil Univ Porto INESC TEC P-4200465 Porto Portugal Univ Porto Fac Engn P-4200465 Porto Portugal

The textile industry is a complex and dynamic system where structured decision-making processes are essential for efficient supply chain management. In this context, mathematical programming models offer a powerful tool for modeling and optimizing the textile supply chain. This systematic review explores the application of mathematical programming models, including linear programming, nonlinear programming, stochastic programming, robust optimization, fuzzy programming, and multi-objective programming, in optimizing the textile supply chain. The review categorizes and analyzes 163 studies across the textile manufacturing stages, from fiber production to integrated supply chains. Key results reveal the utility of these models in solving a wide range of decision-making problems, such as blending fibers, production planning, scheduling orders, cutting patterns, transportation optimization, network design, and supplier selection, considering the challenges found in the textile sector. Analyzing those models, we point out that sustainability considerations, such as environmental and social aspects, remain underexplored and present significant opportunities for future research. In addition, this study emphasizes the importance of incorporating multi-objective approaches and addressing uncertainties in decision-making to advance sustainable and efficient textile supply chain management.

关键词： mathematical programming models Supply chain management Textile industry Review

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mathematical-programming models FOR ENVIRONMENTAL-QUALITY CONTROL

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OPERATIONS RESEARCH 1995年第4期43卷 578-622页

作者： GREENBERG, HJ UNIV COLORADO DEPT ENERGYANALYT GRPDENVERCO 80202 USA

This paper surveys the use of mathematical programming models for controlling environmental quality. The scope includes air, water, and land quality, stemming from the first works in the 1960s. It also includes integrated models, generally that are economic equilibrium models which have an equivalent mathematical program or use mathematical programming to compute a fixed point. A primary goal of this survey is to identify interesting research avenues for people in mathematical programming with an interest in applying it to help control our environment with as little economic sacrifice as possible.

关键词： environment environmental control and economics natural resources air and water quality land contamination waste disposal programming mathematical programming models

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A review of mathematical programming models for strategic capacity planning in manufacturing

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年 153卷 66-85页

作者： Martinez-Costa, Carme Mas-Machuca, Marta Benedito, Ernest Corominas, Albert Inst Org & Control Sistemes Ind IOC Barcelona 08028 Spain Univ Politecn Cataluna Dept Org Empreses E-08028 Barcelona Spain Univ Int Catalunya Dept Org Empreses Barcelona Spain

This paper offers an up-to-date review on strategic capacity planning in manufacturing companies, with two main objectives: (1) to describe and analyze the strategic capacity planning problems;and (2) to review the mathematical programming models proposed in the literature for dealing with these problems. The main search was conducted in the Web of Science using critical keywords and was complemented by using other search engines. Cross checking of citations of all the articles was also carried out. Papers were selected that have formulated discrete time, finite horizon, multi-period models. The major decisions addressed and the main conditioning factors of the strategic capacity problem in the literature are identified and described. A structured overview of the main strategic capacity planning mathematical programming models is given. A classification of the models is proposed and their main characteristics, solution procedures and industrial applications are identified. Based on the review of the existing studies, a framework for capacity planning is presented, consisting of three main phases: problem definition (considering context, characteristics of the manufacturing system and specific factors that could influence the decision-making process), model design and solution procedure. Closing the paper, some future lines of research are suggested. The review should help both practitioners and academic researchers in developing useful models and processes to aid decision-making in strategic capacity planning. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Strategic capacity planning Dynamic capacity planning mathematical programming models

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Integration of decision levels in operating room scheduling problems: Systematic review and proposition of a decision support framework

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COMPUTERS & OPERATIONS RESEARCH 2025年 180卷

作者： de Melo, Igor Eduardo Santos Fogliatto, Flavio Sanson Univ Fed Rio Grande do Sul Ind Engn Dept Ave Osvaldo Aranha 995th Floor BR-90035190 Porto Alegre Brazil

Resource allocation problems are a significant subset of optimization problems widely present in the healthcare industry. Notably, the Operating Room Scheduling Problem (ORSP) is prominent in literature due to its substantial cost and revenue implications. ORSP is structured into three hierarchical decision levels: strategic, tactical and operational, with higher-level decisions influencing subsequent ones. While most studies focus on single decision levels, there has been a growing interest in integrated models, as these offer a more holistic view and often result in better outcomes, despite their complexity of resolution. Although various literature reviews have explored different aspects of ORSP, few have focused on models integrating multiple decision levels. This study addresses that gap by systematically reviewing the literature focusing on contributions presenting mathematical programming models and optimization algorithms that simultaneously address multiple decision levels of the ORSP. Following the PRISMA 2020 protocol, the review spans works published until October 2024, totaling 46 articles. It outlines objectives, characteristics, solution approaches, and identifies gaps in literature. Additionally, a decision framework summarizing the identified integration levels is proposed.

关键词： Resource allocation problems Operating room planning and scheduling Multiple decision level integration mathematical programming models Systematic literature review

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Experimental evaluation of mixed integer programming models for the multi-port master bay plan problem

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FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2015年第2-3期27卷 263-284页

作者： Ambrosino, Daniela Paolucci, Massimo Sciomachen, Anna Univ Genoa Dept Econ & Business Studies Genoa Italy Univ Genoa Dept Informat Bioengn Robot & Syst Engn DIBRIS Genoa Italy Univ Genoa Dept Econ & Business Studies Operat Res Genoa Italy

This paper extends the problem of stowing a given set of different type containers in the available slots of a containership, i.e. the so-called master bay plan problem (MBPP), to the multi-port master bay plan problem (MP-MBPP). MP-MBPP considers the whole route of the ship and the different sets of containers which must be loaded at each port of the route for shipping to successive ports. The sequence of alternate unloading and loading operations is relevant for the effectiveness of stowage plans. This paper introduces two exact mixed integer programming (MIP) models for MP-MBPP, aimed to deal with practical and operative aspects of the problem. It also examines some computationally efficient relaxed formulations of the proposed MIP models and reports an extensive computational experimentation performed on real size instances. The results show the effectiveness of the proposed models and the related resolution methods.

关键词： Maritime logistics Stowage plans mathematical programming models

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Single-site strategic capacity planning considering renewal, maintenance, inventory, taxes and cash flow management

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2016年第7期67卷 970-981页

作者： Benedito, Ernest Corominas, Albert Martinez, Carme Mas-Machuca, Marta Univ Politecn Cataluna Barcelona Spain Univ Int Catalunya Barcelona Spain

This paper deals with strategic capacity planning of a single-site manufacturing system. We propose a MILP model that includes relevant business aspects and possibilities, some of which are only partially or not at all found in the literature. Specifically, we consider decisions on expansion, reduction and renewal of production capacity, and acquisition of storage capacity. In addition, we model aspects such as (a) maintenance costs and unit variable costs depending, respectively, on age and characteristics of facilities, (b) seasonality of the demand and (c) cash flow management, including taxes and, therefore, depreciation of assets. The model maximises the after-tax cash balance at the end of the planning horizon. We also present a computational experiment with 54 instances to show that the model can be solved for a wide range of sizes in a reasonable computing time using comercial software.

关键词： strategic capacity planning manufacturing mathematical programming models

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Container liner fleet deployment: A systematic overview

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2017年 77卷 389-404页

作者： Wang, Shuaian Meng, Qiang Hong Kong Polytech Univ Dept Logist & Maritime Studies Hong Kong Hong Kong Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

Container liner fleet deployment (CLFD) is the assignment of containerships to port rotations (ship routes) for efficient transport of containers. As liner shipping services have fixed schedules, the ship-related operating cost is determined at the CLFD stage. This paper provides a critical review of existing mathematical models developed for the CLFD problems. It first gives a systematic overview of the fundamental assumptions used by the existing CLFD models. The operating characteristics dealt with in existing studies are then examined, including container transshipment and routing, uncertain demand, empty container repositioning, ship sailing speed optimization and ship repositioning. Finally, this paper points out four important future research opportunities: fleet deployment considering ship surveys and inspections, service dependent demand, pollutant emissions, and CLFD for shipping alliances. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Container liner fleet deployment Transshipment Green shipping mathematical programming models

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Freight transportation function in supply chain optimization models: A critical review of recent trends

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EXPERT SYSTEMS WITH APPLICATIONS 2013年第17期40卷 6742-6757页

作者： Jose Bravo, Juan Julio Vidal, Carlos Univ Valle Escuela Ingn Ind Santiago De Cali Colombia

Supply chain mathematical programming models mainly used for computer-aided decision-making processes, have been widely used to date as an advanced support to the experts' opinions. Transportation operations are often a central aspect of such models. We developed a detailed review of the freight transportation function included in supply chain models, and some transportation aspects were identified and analyzed in recent articles (2009-2013). We identified one paradigm, two trends and an anomaly regarding transportation modeling. The main anomaly-related observation refers to the absence of correspondence between the modeling of transportation operations and the transportation cost function considered in the models. This gap has not been so far considered in the literature and we propose a framework to guide, in a more systemic way, the transportation considerations into optimization models. In addition, some concerns regarding trade-off analysis, private/outsourced fleet considerations, the role of time and distance in transportation cost analysis, among others, were also included. These issues are expected to be significant for supply chain analysts whose decisions emerge from modeling and computer-aided tools. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Freight transportation function In-land transportation Supply chain Transportation cost mathematical programming models Critical review

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An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning

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COMPUTERS IN INDUSTRY 2011年第5期62卷 519-540页

作者： Alemany, M. M. E. Alarcon, F. Lario, Fco-Cruz Juan Boj, Jorge Univ Politecn Valencia Ctr Invest Gestio & Engn Prod CIGIP Cami de Vera S-N Valencia 46022 Spain

In the context of supply chains operations planning, mathematical programming models have been mainly used for centralised decision-making. However, the supply chain (SC) members not always agree on the alignment of individual decisions to SC-wide objectives and are usually reluctant to share all the required SC-wide information. For these reasons, SC decentralised decision making, in which different decisional units have to be coordinated to achieve a certain level of SC performance, is the most usual situation. In this collaborative planning (CP) context, spatial and temporal integration among the different SC decisional parts has to be considered. This paper aims to develop an application which supports the integrated modelling and execution of the CP decision-making process in SCs made up of several decisional centres (DCs) which make decisions based on mathematical programming models (as in Advanced Planning Systems) under temporal and spatial integration. The described application has been used to assist the CP of a real ceramic SC. The results are also reported. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Application Collaborative planning Supply chain Temporal and spatial integration mathematical programming models

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Radio planning and coverage optimization of 3G cellular networks

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WIRELESS NETWORKS 2008年第4期14卷 435-447页

作者： Amaldi, Edoardo Capone, Antonio Malucelli, Federico Politecn Milan Dipartimento Elettron & Informaz I-20133 Milan Italy

Radio planning and coverage optimization are critical issues for service providers and vendors that are deploying third generation mobile networks and need to control coverage as well as the huge costs involved. Due to the peculiarities of the Code Division Multiple Access (CDMA) scheme used in 3G cellular systems like UMTS and CDMA2000, network planning cannot be based only on signal predictions, and the approach relying on classical set covering formulations adopted for second generation systems is not appropriate. In this paper we investigate mathematical programming models for supporting the decisions on where to install new base stations and how to select their configuration (antenna height and tilt, sector orientations, maximum emission power, pilot signal, etc.) so as to find a trade-off between maximizing coverage and minimizing costs. The overall model takes into account signal-quality constraints in both uplink and downlink directions, as well as the power control mechanism and the pilot signal. Since even small and simplified instances of this NP-hard problem are beyond the reach of state-of-the-art techniques for mixed integer programming, we propose a Tabu Search algorithm which provides good solutions within a reasonable computing time. Computational results obtained for realistic instances, generated according to classical propagation models, with different traffic scenarios (voice and data) are reported and discussed.

关键词： 3G UMTS CDMA2000 radio planning base stations location configuration signal quality constraint mathematical programming models Tabu Search

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