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Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2014年第3期236卷 863-878页

作者： Rieck, Julia Ehrenberg, Carsten Zimmermann, Juergen Tech Univ Clausthal Inst Management & Econ Operat Res Grp D-38678 Clausthal Zellerfeld Germany

In this paper, we consider a variant of the many-to-many location-routing problem, where hub facilities have to be located and customers with either pickup or delivery demands have to be combined in vehicle routes. In addition, several commodities and inter-hub transport processes are taken into account. A practical application of the problem can be found in the timber-trade industry, where companies provide their services using hub-and-spoke networks. We present a mixed-integer linear model for the problem and use CPLEX 12.4 to solve small-scale instances. Furthermore, a multi-start procedure based on a fix-and-optimize scheme and a genetic algorithm are introduced that efficiently construct promising solutions for medium- and large-scale instances. A computational performance analysis shows that the presented methods are suitable for practical application. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Location-routing Inter-hub transport Multi-commodity pickup-and-delivery Mixed-integer linear programming fix-and-optimize Genetic algorithm

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The time window assignment vehicle routing problem with product dependent deliveries

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2018年第Aug.期116卷 163-183页

作者： Neves-Moreira, Fabio da Silva, Diogo Pereira Guimaraes, Luis Amorim, Pedro Almada-Lobo, Bernardo Univ Porto INESC TEC Rua Dr Roberto Frias P-4200465 Porto Portugal Univ Porto Fac Engn Rua Dr Roberto Frias P-4200465 Porto Portugal LTP Labs Rua Doutor Julio de Maros P-4200355 Porto Portugal

This paper presents a new formulation for a time window assignment vehicle routing problem where time windows are defined for multiple product segments. This two-stage stochastic optimization problem is solved by means of a fix-and-optimize based matheuristic. The first stage assigns product dependent time windows while the second stage defines delivery schedules. Our approach outperforms a general-purpose solver and achieves an average cost decrease of 5.3% over expected value problem approaches. Furthermore, a sensitivity analysis on three operational models shows that it is possible to obtain significant savings compared to the solutions provided by a large European food retailer.

关键词： Retail operations Vehicle routing Time window assignment Multiple product deliveries fix-and-optimize Stochastic optimization

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Mixed integer programming based heuristics for the Patient Admission Scheduling problem

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COMPUTERS & OPERATIONS RESEARCH 2017年第Apr.期80卷 38-49页

作者： Turhan, Aykut Melih Bilgen, Bilge Dokuz Eylul Univ Grad Sch Nat & Appl Sci Dept Ind Engn Tinaztepe Campus TR-35160 Izmir Turkey Dokuz Eylul Univ Dept Ind Engn Tinaztepe Campus TR-35160 Izmir Turkey

The Patient Admission Scheduling (PAS) problem is a combinatorial optimization problem where elective patients are automatically assigned to beds for the duration of their stay considering not only the medical necessity but also the patient preferences. Due to its combinatorial nature, solving the previously published problem instances to optimality is a difficult task. In this paper, we present two Mixed Integer Programming (MIP) based heuristics namely fix-and-Relax (F&R) and fix-and-optimize (F&O) where PAS problem instances are decomposed into sub-problems and then the sub-problems are optimized. Our approach uses patient decomposition considering patient length-of-Stay (LoS), room preference, admission date, specialism choice, and age, as well as time decomposition considering different optimization window sizes. Quick solutions generated by F&R heuristic are used as an input to the F&O heuristic and are improved in an iterative nature. Main goal of the study is to provide high quality solutions in shorter run times. Computational findings show that the proposed heuristics provide promising results towards the solution of the problem in faster CPU times than the previously reported values where less than 15 percent gap from the best known solutions is achieved for most of the test instances, and as low as 5 percent gap for some of the sample data. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： OR In Health Services Patient Admission Scheduling MIP based heuristics fix-and-Relax fix-and-optimize

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A parallelized matheuristic for the International Timetabling Competition 2019

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JOURNAL OF SCHEDULING 2022年第4期25卷 429-452页

作者： Mikkelsen, Rasmus O. Holm, Dennis S. Tech Univ Denmark DTU Management AkademivejBldg 358 DK-2800 Lyngby Denmark

The International Timetabling Competition 2019 (ITC 2019) presents a novel and generalized university timetabling problem composed of traditional class time and room assignment and student sectioning. In this paper, we present a parallelized matheuristic tailored to the ITC 2019 problem. The matheuristic is composed of multiple methods using the graph-based mixed-integer programming (MIP) model defined for the ITC 2019 problem by Holm et al. (A graph-based MIP formulation of the International Timetabling Competition 2019. J Sched, 2022. hups://***/10.1007/s10951-022-00724-y) . We detail all methods included in the parallelized matheuristic and the collaboration between them. The parallelized matheuristic includes two methods for producing initial solutions and uses a fix-and-optimize matheuristic to improve solutions. Additionally, the method uses the full MIP model to calculate lower bounds. We describe how the methods perform collaboratively through solution sharing, and a diversification scheme invoked when the search stagnates. Furthermore, we explain how we decompose the problem for instances with a large number of students. We evaluate components of the parallelized matheuristic using the 30 benchmark instances of the ITC 2019. The complete parallelized matheuristic performs well, even solving some instances to proven optimality. The presented method is the winning algorithm of the competition, further demonstrating its quality.

关键词： Mixed-integer programming Parallelized matheuristic fix-and-optimize University timetabling International Timetabling Competition 2019 ITC 2019

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Energy efficient production planning and scheduling problem with processing technology selection

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年第0期132卷 260-270页

作者： Liang, Jingran Wang, Yuyan Zhang, Zhi-Hai Sun, Yiqi Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China

Energy efficiency attains increasing attention in production systems due to growing energy costs and public perception of environmentally conscious operations. The paper features a capacitated production planning and scheduling problem (CPPS) with sequence-dependent setups for a continuous production line. Meanwhile, energy consumption costs associated with process techniques selection decisions are incorporated into the CPPS. A fix-and-optimize solution approach is proposed to solve the problem. Extensive computational experiments reveal an advantage of the proposed approach having a stable computational performance in solution quality. The optimal results also show the energy cutting benefits of the integrated decision considering operations and energy costs. Moreover, a case study of tea drink production line is presented to demonstrate the application of the model and the solution approach.

关键词： Energy efficient manufacturing Capacitated production planning and scheduling Mixed integer linear programming fix-and-optimize

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A matheuristic approach for the b-coloring problem using integer programming and a multi-start multi-greedy randomized metaheuristic

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2021年第1期295卷 66-81页

作者： Melo, Rafael A. Queiroz, Michell F. Santos, Marcio C. Univ Fed Bahia Computat Intelligence & Optimizat Res Lab CInO Dept Ciencia Computacao Salvador BA Brazil Univ Fed Ceara Campus Russas Rua Felipe Santiago BR-62900000 Russas CE Brazil

Given a graph G = (V, E) , the b-coloring problem consists in attributing a color to every vertex in V such that adjacent vertices receive different colors, every color has a b-vertex, and the number of colors is maximized. A b-vertex is a vertex adjacent to vertices colored with all used colors but its own. The b- coloring problem is known to be NP-Hard and its optimal solution determines the b-chromatic number of G, denoted X-b(G). This paper presents an integer programming formulation and a very effective multi-greedy randomized heuristic which can be used in a multi-start metaheuristic. In addition, a matheuris-tic approach is proposed combining the multi-start multi-greedy randomized metaheuristic with a MIP (mixed integer programming) based local search procedure using the integer programming formulation. Computational experiments establish the proposed multi-start metaheuristic as very effective in generating high quality solutions, along with the matheuristic approach successfully improving several of those results. Moreover, the computational results show that the multi-start metaheuristic outperforms a state-of-the-art hybrid evolutionary metaheuristic for a subset of the large instances which were previously considered in the literature. An additional contribution of this work is the proposal of a benchmark in-stance set, which consists of newly generated instances as well as others available in the literature for classical graph problems, with the aim of standardizing computational comparisons of approaches for the b-coloring problem in future works. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Metaheuristics Graph b-coloring Integer programming fix-and-optimize Matheuristics

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A lot-sizing and scheduling model for multi-stage flow lines with zero lead times

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2013年第3期225卷 404-419页

作者： Stadtler, Hartmut Sahling, Florian Univ Hamburg Inst Logist & Transport Hamburg Germany Leibniz Univ Hannover Inst Prod Wirtschaft D-30167 Hannover Germany

We present a new model formulation for lot-sizing and scheduling of multi-stage flow lines which works without a fixed lead-time offset and still guarantees a feasible material flow. In the literature, multi-stage lot-sizing model formulations often use a fixed lead time offset of one period leading to increased planned lead times. Computational tests have shown that the total costs resulting from our new model formulation are at least 10% lower. Furthermore, we present a solution approach based on fix-and-Relax and fix-and-optimize. Numerical results show that this solution approach generates high-quality solutions in moderate computational time. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Lot-sizing Scheduling Zero lead time offset fix-and-optimize

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Solving a large multi-product production-routing problem with delivery time windows

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2019年 86卷 154-172页

作者： Neves-Moreira, Fabio Almada-Lobo, Bernardo Cordeau, Jean-Francois Guimaraes, Luis Jans, Raf Univ Porto INESC TEC P-4200 Porto Portugal Univ Porto Fac Engn P-4200 Porto Portugal HEC Montreal 3000 Chemin Cote St Catherine Montrueal PQ Canada CIRRELT 3000 Chemin Cote St Catherine Montrueal PQ Canada

Even though the joint optimization of sequential activities in supply chains is known to yield significant cost savings, the literature concerning optimization approaches that handle the real-life features of industrial problems is scant. The problem addressed in this work is inspired by industrial contexts where vendor-managed inventory policies are applied. In particular, our study is motivated by a meat producer whose supply chain comprises a single meat processing centre with several production lines and a fleet of vehicles that is used to deliver different products to meat stores spread across the country. A considerable set of characteristics, such as product family setups, perishable products, and delivery time windows, needs to be considered in order to obtain feasible integrated plans. However, the dimensions of the problem make it impossible to be solved exactly by current solution methods. We propose a novel three-phase methodology to tackle a large Production-Routing Problem (PRP) combining realistic features for the first time. In the first phase, we attempt to reduce the size of the original problem by simplifying some dimensions such as the number of products, locations and possible routes. In the second phase, an initial PRP solution is constructed through a problem decomposition comprising several inventory-routing problems and one lot-sizing problem. In the third phase, the initial solution is improved by different mixed-integer programming models which focus on small parts of the original problem and search for improvements in the production, inventory management and transportation costs. Our solution approach is tested both on simpler instances available in the literature and on real-world instances containing additional details, specifically developed for a European company's case study. By considering an integrated approach, we achieve global cost savings of 21.73% compared to the company's solution. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Production-routing Time windows Perishability fix-and-optimize Matheuristic Case study

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A long-haul freight transportation problem: Synchronizing resources to deliver requests passing through multiple transshipment locations

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第2期248卷 487-506页

作者： Neves-Moreira, F. Amorim, P. Guimaraes, L. Almada-Lobo, B. Univ Porto INESC TEC P-4200465 Oporto Portugal Univ Porto Fac Engn P-4200465 Oporto Portugal

This research aims at tackling a real-world long-haul freight transportation problem where tractors are allowed to exchange semi-trailers through several transshipment points until a request reaches its destiny. The unique characteristics of the considered logistics network allow for providing long-haul services by means of short-haul jobs, drastically reducing empty truck journeys. A greater flexibility is achieved with faster responses. Furthermore, the planning goals as well as the nature of the considered trips led to the definition of a new problem, the long-haul freight transportation problem with multiple transshipment locations. A novel mathematical formulation is developed to ensure resource synchronization while including realistic features, which are commonly found separately in the literature. Considering the complexity and dimension of this routing and scheduling problem, a mathematical programming heuristic (matheuristic) is developed with the objective of obtaining good quality solutions in a reasonable amount of time, considering the logistics business context. We provide a comparison between the results obtained for 79 real-world instances. The developed solution method is now the basis of a decision support system of a Portuguese logistics operator (LO). (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.

关键词： Transportation Tractor-and-trailer Resource synchronization fix-and-optimize Case-study

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BFO: a hybrid bees algorithm for the multi-level capacitated lot-sizing problem

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JOURNAL OF INTELLIGENT MANUFACTURING 2017年第4期28卷 929-944页

作者： Furlan, Marcos Mansano Santos, Maristela Oliveira Univ Sao Paulo Inst Ciencias Matemat & Comp Dept Matemat Aplicada & Estat Caixa Postal 668 BR-13560970 Sao Carlos SP Brazil

This paper presents a hybrid heuristic based on the bees algorithm combined with the fix-and-optimize heuristic to solve the multi-level capacitated lot-sizing problem. The bees algorithm can be used as a new method to determine the sequence in which to apply the partition in the fix-and-optimize approach. This new manner of choosing the partition adds diversity to the solution pool and yields different local optima solutions after some iterations. The bees-and-fix-and-optimize (BFO) algorithm attempts to avoid these local optima by performing random search in accordance with the concept of bees algorithm. The BFO has yielded good results for instances from the literature and, in most cases, the results are superior to the best results provided by approaches presented in recent literature. They show that this construction concept is advantageous and illustrate the efficiency of hybrid methods composed of matheuristics and metaheuristics. Furthermore, the BFO approach is a general-purpose heuristic that can be applied to solve other types of production planning problems.

关键词： Lot-sizing problem Multi-level problem Bees algorithm fix-and-optimize

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