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Sustainable open vehicle routing with release-time and time-window: A two-echelon distribution system

IFAC-PapersOnLine 2019年第13期52卷 571-576页

作者： Babagolzadeh, M. Shrestha, A. Abbasi, B. Zhang, S. Atefi, R. Woodhead, A. School of Commerce University of Southern Queensland ToowoombaQLD Australia School of Management and Enterprise University of Southern Queensland ToowoombaQLD Australia School of Business IT and Logistics RMIT University Melbourne Australia Department of Industrial Engineering Ferdowsi university of Mashhad Mashhad Iran University of Southern Queensland ToowoombaQLD Australia

In an increasingly competitive economic environment, outsourcing for logistics has emerged as a cost-efficient strategy during freight transportation. The open vehicle routing problem is a type of classical vehicle routing problem, in which businesses outsource logistics to a third-party company and the vehicles do not return to the depot at the end of their journey. This paper develops a mixed integer linear programming model for two-echelon open vehicle routing problem that integrates city distribution constraints such as time-window and release-time. The release-time refers to the time at which products become ready at satellites for downstream distribution, and it is influenced by limited available resources and work load of each satellite. The proposed model determines the optimal configuration of the routes while minimizing the handling costs, penalty costs, and transportation costs. We use a comprehensive emission model that accounts for load, distance, speed and vehicle characteristics to estimate fuel consumption. Finally, we utilize a numerical example to illustrate the proposed model and explore the effects of release-time on total cost. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Vehicle routing Freight transportation integer programming Supply chains Vehicles Distribution systems mixed integer linear programming model Open vehicle routing problems Release time Sustainable supply chains Time windows Vehicle characteristics Vehicle Routing Problems

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An improved flow-based formulation and reduction principles for the minimum connectivity inference problem

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OPTIMIZATION 2019年第10期68卷 1963-1983页

作者： Dar, Muhammad Abid Fischer, Andreas Martinovic, John Scheithauer, Guntram Tech Univ Dresden Fac Math Inst Numer Math Dresden Germany

The Minimum Connectivity Inference (MCI) problem represents an -hard generalization of the well-known minimum spanning tree problem and has been studied in different fields of research independently. Let an undirected complete graph and finitely many subsets (clusters) of its vertex set be given. Then, the MCI problem is to find a minimal subset of edges so that every cluster is connected with respect to this minimal subset. Whereas, in general, existing approaches can only be applied to find approximate solutions or optimal edge sets of rather small instances, concepts to optimally cope with more meaningful problem sizes have not been proposed yet in literature. For this reason, we present a new mixed integer linear programming formulation for the MCI problem, and introduce new instance reduction methods that can be applied to downsize the complexity of a given instance prior to the optimization. Based on theoretical and computational results both contributions are shown to be beneficial for solving larger instances.

关键词： Minimum connectivity inference reduction rules mixed integer linear programming model subset interconnection design

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model of decision support for the configuration of manufacturing system

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IFAC-PapersOnLine 2019年第13期52卷 826-831页

作者： Wikarek, Jaroslaw Sitek, Pawel Nielsen, Peter Institute of Management and Control Systems Kielce University of Technology Al. 1000-lecia PP 7 Kielce25-314 Poland Dept. of Materials and Production Aalborg University Aalborg Denmark

Manufacturing enterprises today have to face the volatility of markets, characterized by a decreasing production volume and an increasing number of product variants to meet customer expectations. Traditional dedicated manufacturing lines (DML) have been replaced by flexible manufacturing systems (FMS) and, recently, by the systems that combine features of DML and FMS, i.e., by reconfigurable manufacturing systems (RMS). Appropriate manufacturing support and optimization systems for FMS and RMS will advance the quality and effectiveness of reconfigurable manufacturing. This paper proposes an original mixed integer linear programming (MILP) model for decision support in configuration and reconfiguration of the manufacturing system. The modeled problem is a certain development of the known machine loading problem MLP. In this approach, we generate a highly parameterized model based on a set of constraints and a set of questions. Different mathematical programming (MP) - based solvers are proposed to solve this model. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Flexible manufacturing systems Computer aided manufacturing Decision support systems integer programming Mathematical programming Optimization Customer expectation Decision supports Machine loading problems Manufacturing enterprise Manufacturing lines mixed integer linear programming model Reconfigurable manufacturing Reconfigurable manufacturing system

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Solving a real bi-objective skilled agent assignment problem in the service-to-business domain, considering both economic efficiency and agent satisfaction

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IFAC-PapersOnLine 2019年第13期52卷 2026-2031页

作者： Doan, M.P. Fondrevelle, J. Botta-Genoulaz, V. Ribeiro, J.F.F. Univ Lyon INSA-Lyon DISP EA4570 Villeurbanne cedex69621 France University of Sao Paulo USP-FEARP-RAD Ribeirao Preto SP14040-905 Brazil

In this article, we introduce a mixed integer linear programming (MILP) model for a real bi-objective agent assignment problem in the service-to-business domain. Agents with different skill types, skill levels and work contract types have to be assigned to tasks required by clients. Tasks usually require a big number of agents but this number is stable over time. Choosing the assignment, the company has two important objectives to attain including minimizing the global travel costs and maximizing the satisfaction level of its agents related to their average work trip duration. Based on the MILP model proposed, we perform some experiments on a real database provided by a Brazilian partner. These experiments allow us to study the interactions between the objectives, and the impact of some important characteristics on the solutions of the problem. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： integer programming Combinatorial optimization Multiobjective optimization Personnel Activity scheduling Assignment problems Business domain Economic efficiency MILP model mixed integer linear programming model Skilled personnel Workforce assignment

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Bi-objective optimization for Scheduling and Multi-skilled Worker Assignments in the Hybrid Flow Shop

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IFAC-PapersOnLine 2019年第13期52卷 2128-2133页

作者： Liu, Ming Yang, Xuenan School of Economics and Management Tongji University Shanghai200092 China

This paper investigate a bi-objective scheduling and worker assignment problem in a hybrid flow shop. The difficulty of this problem lies in four aspects: (i) the workers differ with each other in both the quantity and proficiency of their acquired skilles; (ii) each processing stage is comprised of parallel unrelated machines; (iii) sequence dependent setup time should be considered and respected; (iv) both the makespan and the total flow time should be minimized simultaneously. To solve this bi-objective optimization problem, we first formulate it into a mixed integer linear programming model, then the commonly used exact solution method Ε-constraint method is adopted to solve the model. A small instance is randomly generated and tested, the testing result demonstrates the effectiveness of the proposed model. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： integer programming Combinatorial optimization Machine shop practice Scheduling Bi objectives Bi objective optimization Epsilon constraint method Hybrid flow shop mixed integer linear programming model Sequence dependent setup time Skilled workers Worker assignments

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An integrated production inventory routing problem for multi perishable products with fuzzy demands and time windows

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IFAC-PapersOnLine 2019年第13期52卷 523-528页

作者： Ghasemkhani, A. Tavakkoli-Moghaddam, R. Shahnejat-Bushehri, S. Momen, S. Tavakkoli-Moghaddam, H. School of Industrial Engineering College of Engineering University of Tehran Tehran Iran Arts et Métiers ParisTech LCFC Metz France School of Industrial and Systems Engineering Tarbiat Modares University Tehran Iran

This paper presents an integrated production inventory routing problem with a mixed integer linear programming (MILP) model that remarks a multi-product, multi-period with heterogeneous fleets and time windows in a distribution network. In particular, this research differs because of the limited lifetime of products, demand uncertainty and integration of production-inventory-routing. Two fuzzy approaches define the uncertainty in the demand of retailers. The objective of the proposed model is to maximize the total profit, which equals the selling revenue subtract the aggregation of the holding, production, transportation and driver wage costs. Randomly generated instances are used to validate the effectiveness and the intricacy of the model, which is solved by the linear programming solver CPLEX. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： integer programming Fuzzy systems Demand uncertainty Fuzzy approach Heterogeneous fleet Integrated production linear programming solvers mixed integer linear programming model Perishable product Production inventories

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Dual resource constrained scheduling for quality control laboratories

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IFAC-PapersOnLine 2019年第13期52卷 1421-1426页

作者： Cunha, Mariana M. Viegas, Joaquim L. Martins, Miguel S.E. Coito, Tiago Costigliola, Andrea Figueiredo, João Sousa, João M.C. Vieira, Susana M. IDMEC Instituto Superior Técnico Universidade de Lisboa Portugal Hovione FarmaCiencia S.A Lisbon Portugal IDMEC Universidade de Évora Évora Portugal

This work presents a novel formulation for quality control laboratory scheduling considering both equipment and analysts as constraints. The problem is modelled as a dual-resource constrained flexible job shop problem. The formulation considers analyst tasks at different times during the processing of samples. The problem is formulated as a mixed integer linear programming model (MILP) aiming to minimise makespan. Two sets of instances for the scheduling problem are proposed. The first instance consists of a small example that illustrates the proposed formulation and is solved to optimality. The second instance mimics the real industrial problem and shows the challenges resulting from growing complexity. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Quality control integer programming Job shop scheduling Quality assurance Research laboratories Scheduling Control Laboratory Dual resource constrained Flexible job shops Flexible job shop problem Industrial problem mixed integer linear programming mixed integer linear programming model Scheduling problem

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A Multi-objective Sustainable Medicine Supply Chain Network Design Using a Novel Hybrid Multi-objective Metaheuristic Algorithm

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INTERNATIONAL JOURNAL OF ENGINEERING 2020年第10期33卷 1986-1995页

作者： Goodarzian, F. Hosseini-Nasab, H. Fakhrzad, M. B. Yazd Univ Dept Ind Engn Yazd Iran

End-of-life products have a severe impact on the ecological system. Potential production policies and distribution strategies for the newly manufactured product have attracted significant attention to sustainable development. Sustainability in supply chain management has much importance to achieve eco-friendly goals. In this study, we have developed sustainable objectives in the supply chain optimization framework with different constraints. The trade-off between economic, environmental and social effects objectives have identified by ensuring the optimal allocation of different products among various levels. In this regard, a new sustainability multi-objective mixed-integer linear programming mathematical model in the medicine supply chain network is developed. Although the proposed model is an NP-hard problem, we develop a novel hybrid Particle Swarm Optimization and Genetic Algorithm to achieve Pareto solutions. Then, to adjust the important parameters of the algorithms and chose the optimum levels of the significant factors for more efficiency is employed the Taguchi method. The results show that the economic and environmental effects tend to be decreased and the social impacts tend to be increased in the medicine supply chain network which can exhibit the best sustainability performance. The various outcomes of numerical experiments indicate that the proposed solution algorithm is more reliable than other algorithms. The solution methods are complemented with several sensitivity analyses on the input parameters of the model.

关键词： Medicine Supply Chain Network Sustainability mixed integer linear programming model Multi-objective Problems Hybrid Metaheuristic Algorithm Taguchi Method

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Optimizing a sustainable logistics problem in a renewable energy network using agenetic algorithm

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OPSEARCH 2019年第1期56卷 73-90页

作者： Sadeghi, Javad Haapala, Karl R. Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97331 USA

Renewable energy sources, including bio-energy technologies, have been introduced to overcome sustainability challenges, such as negative environmental impacts and energy insecurity due to reliance on fossil fuels. Logistics activities have a significant effect on the cost and environmental impacts of renewable energy supply chains. Understanding and reducing the carbon footprint of renewable energy supply chains can aid in mitigating environmental impacts. Thus, this research presents a mathematical model that can be used to optimize renewable energy supply chain logistics costs and carbon footprint. The proposed model considers a biomass-to-bio-oil supply chain, including harvesting and collection sites, bio-refineries, and distribution centers. It is assumed that mobile and fixed refineries will be used to produce bio-oil. The model considers the mass of biomass and bio-oil, number of mobile and fixed refineries, and number of truck trips to minimize total cost, where a carbon tax is used to represent carbon footprint in the mathematical cost model. A genetic algorithm is designed to obtain a near-optimal solution. Six scenarios for mobile and fixed refinery capacity are tested in performing sensitivity analysis of the model. The results indicate that the mathematical model of the bio-oil supply chain has reasonable relationships between input and output variables. The model is able to incorporate the impact of carbon emissions in a mixed-refinery bio-oil supply chain as a cost parameter. It was also found that increasing mobile refinery capacity has the greater effect on reducing total cost and carbon emissions than increasing fixed refinery capacity.

关键词： Sustainable supply chains management Carbon tax Genetic algorithm mixed integer linear programming model

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An appointment scheduling framework to balance the production of blood units from donation

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第3期265卷 1124-1143页

作者： Bas, Seda Carello, Giuliana Lanzarone, Ettore Yalcindag, Semih Yeditepe Univ Ind & Syst Engn Dept Istanbul Turkey Politecn Milan DEIB Milan Italy CNR IMATI Milan Italy

Blood is fundamental in several care treatments and surgeries, and plays a crucial role in the health care system. It is a limited resource, as it can be produced only by donors and its shelf life is short;thus, the blood donation (BD) system aims at providing adequate supply of blood units to transfusion centers and hospitals. An effective collection of blood units from donors is fundamental for adequately feeding the entire BD system and optimizing blood usage. However, despite its relevance, donation scheduling is only marginally addressed in the literature. In this paper we consider the Blood Donation Appointment Scheduling (BDAS) problem, aiming at balancing the production of the different blood types among days in order to provide a quite constant feeding of blood units to the BD system. We propose a framework for the appointment reservation that accounts for both booked donors and donors arriving without a reservation. It consists of an offline mixed integer linear programming (MILP) model for preallocating time slots to blood types, and an online prioritization policy to assign a preallocated slot when the donor calls to make the reservation. (C) 2017 Elsevier B.V. All rights reserved.

关键词： OR in health systems Blood Donation Appointment Scheduling Production balancing mixed integer linear programming model Offline and online procedure

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