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Whole blood or apheresis donations? A multi-objective stochastic optimization approach

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第1期266卷 193-204页

作者： Osorio, Andres F. Brailsford, Sally C. Smith, Honora K. Univ Southampton Southampton Business Sch Southampton SO17 1BJ Hants England Univ Icesi Calle 18 122-135 Cali Colombia Univ Southampton Math Sci Southampton SO17 1BJ Hants England

In the blood supply chain, several alternative technologies are available for collection and processing. These technologies differ in cost and efficiency: for example, collection by apheresis requires very expensive machines but the yield of blood products is considerably greater than whole blood collection. Blood centre managers are faced with the difficult strategic problem of choosing the best combination of technologies, as well as the equally difficult operational problem of assigning donors to collection methods. These decisions are complex since so many factors have to be taken into account, including stochastic demand, blood group compatibilities, donor availability, the proportions of blood types in both donor and recipient populations, fixed and variable costs, and process efficiencies. The use of deterministic demand forecasts is rarely adequate and a robust decision must consider uncertainty and variability in demand as well as trade-offs between several potentially conflicting objectives. This paper presents a multi-objective stochastic integer linear programming model to support such decisions. The model treats demand as stochastic and seeks to optimize two objectives: the total cost and the number of donors required. To solve this problem, we apply a novel combination of Sample Average Approximation and the Augmented Epsilon-Constraint algorithm. This approach is illustrated using real data from Bogota, Colombia. (C) 2017 Elsevier B.V. All rights reserved.

关键词： OR in health services Blood supply chain Blood fractionation Stochastic programming multiple objective programming

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A multiple objective transportation problem approach to dynamic truck dispatching in surface mines

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第1期276卷 331-342页

作者： Afrapoli, Ali Moradi Tabesh, Mohammad Askari-Nasab, Hooman Univ Alberta Dept Civil & Environm Engn MOL Edmonton AB T6G 2W2 Canada

In surface mining operations, fleet management systems seek to make optimal decisions to handle material in two steps: path production optimization and real-time truck dispatching. This paper develops a multiple objective transportation model for real-time truck dispatching. The model addresses two major drawbacks of former models. The proposed model dispatches the trucks to destinations trying to simultaneously minimize shovel idle times, truck wait times, and deviations from the path production requirements established by the production optimization stage. To evaluate the performance of the proposed model, we developed a benchmark model based on the backbone of the most widely used fleet management system in the mining industry (Modular Mining DISPATCH). Afterward, we built a discrete event simulation model of the truck and shovel operation using an iron ore mine case study, implemented both of the dispatching models, and compared the results. The implementation of the models suggests that the multiple objective model developed in this paper is able to meet the production requirements of the operation using a fleet at 85% of the size of the deterministically calculated desired fleet. In addition, the model is able to meet the full capacity of the processing plants with a fleet of 30% less trucks than the desired fleet. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Simulation multiple objective programming Goal programming Truck dispatching Fleet management system

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Multiobjective optimization using an adaptive weighting scheme

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OPTIMIZATION METHODS & SOFTWARE 2016年第1期31卷 110-133页

作者： Deshpande, Shubhangi Watson, Layne T. Canfield, Robert A. Virginia Polytech Inst & State Univ Dept Comp Sci Blacksburg VA 24061 USA Virginia Polytech Inst & State Univ Dept Comp Math Blacksburg VA 24061 USA Virginia Polytech Inst & State Univ Dept Aerosp & Ocean Engn Blacksburg VA 24061 USA

A new Pareto front approximation method is proposed for multiobjective optimization problems (MOPs) with bound constraints. The method employs a hybrid optimization approach using two derivative-free direct search techniques, and intends to solve black box simulation-based MOPs where the analytical form of the objectives is not known and/or the evaluation of the objective function(s) is very expensive. A new adaptive weighting scheme is proposed to convert a multiobjective optimization problem to a single objective optimization problem. Another contribution of this paper is the generalization of the star discrepancy-based performance measure for problems with more than two objectives. The method is evaluated using five test problems from the literature, and a realistic engineering problem. Results show that the method achieves an arbitrarily close approximation to the Pareto front with a good collection of well-distributed nondominated points for all six test problems.

关键词： multiple objective programming DIRECT MADS surrogates triangulation

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Computational complexity of convoy movement planning problems

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MATHEMATICAL METHODS OF OPERATIONS RESEARCH 2015年第1期82卷 31-60页

作者： Gopalan, Ram Rutgers State Univ Sch Business Camden NJ 08102 USA

Convoy movement planning problems arise in a number of important logistical contexts, including military planning, railroad optimization and automated guided vehicle routing. In the convoy movement problem (CMP), a set of convoys, with specified origins and destinations, are to be routed with the objective of minimizing either makespan or total flow time, while observing a number of side constraints. This paper characterizes the computational complexity of several restricted classes of CMPs. The principal objective is to identify the most parsimonious set of problem features that make the CMP intractable. A polynomial-time algorithm is provided for the single criterion two-convoy movement problem. The performance of a simple prioritization-idling approximation algorithm is also analyzed for the K-convoy movement problem. Error bounds are developed for the makespan and flow time objectives.

关键词： Complexity theory Logistics multiple objective programming Convoy routing Approximation algorithms

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On the potential balance among compulsory education outcomes through econometric and multiobjective programming analysis

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第2期241卷 527-540页

作者： Luque, M. Marcenaro-Gutierrez, O. D. Lopez-Agudo, L. A. Univ Malaga Dept Appl Econ Math E-29071 Malaga Spain Univ Malaga Dept Appl Econ Stat & Econometr E-29071 Malaga Spain

This paper sheds new light on the relationship between inputs and outputs in the framework of the educational production function. In particular, it is geared at gaining a better understanding of which factors may be affected in order to achieve an optimal educational output level. With this objective in mind, we analyze teacher-based assessments (actual marks) in three different subjects using a multiobjective schema. For much of the analysis we use data from a recent (2010) Survey - ESOC10, linked with the results from an educational assessment program conducted among 11 and 15 year-old students and with the administrative records on teacher-based scores. Following the statistical and econometric analysis of these data, they are used to build a multiobjective mixed integer model. A reference point approach is used to determine the profile of, potentially, the most "successful and balanced" students in terms of educational outcomes. This kind of methodology in multiobjective programming allows generating "very balanced" solutions in terms of the objective values (subjects). Finally, a sensitivity analysis is used to determine policies that can be carried out in order to improve the performance levels of primary and secondary education students. Particularly, policy makers should be more concerned with the need to promote some cultural habits - such as reading -, from both the students' and parents' side. Additionally, policy efforts should be focused on making the vocational pathways available to Spanish youth more appealing, with the aim of taking advantage of the particular skills of students not succeeding in the academic track. (C) 2014 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Education Students performance Reference point Econometric analysis

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Constraint programming for multi-line parallel partial disassembly line balancing problem with optional common stations

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APPLIED MATHEMATICAL MODELLING 2023年第1期122卷 435-455页

作者： Zhang, Yu Zhang, Zeqiang Zeng, Yanqing Wu, Tengfei Southwest Jiaotong Univ Sch Mech Engn Chengdu 610031 Peoples R China Technol & Equipment Rail Transit Operat & Maintena Chengdu 610031 Peoples R China

Due to the increased demand for efficient recycling systems for end-of-life (EOL) products, the role of disassembly lines in reverse supply chains has become crucial. Parallel disassembly lines can handle multi-type EOL products and consist of two or more lines. However, previous research has primarily focused on two-line disassembly systems and has not fully addressed the optionality of common stations. To address this gap, this study proposes three exact methods for optimizing multi-line parallel disassembly systems with optional common stations, partial disassembly mode, and AND/OR precedence relations. Firstly, a mixed-integer linear programming (MILP) model is formulated that optimizes three objectives: weighted line length, additional profits, and hazard evaluation. Secondly, two constraint programming (CP) models are developed with different solution methodologies to provide more extensive applications and efficient solutions. An illustrative example shows that production mode can significantly reduce line length and workstations, and computational results demonstrate that both CP methods outperform the MILP model in terms of solution quality and computational efficiency. Specifically, the CP-I method demonstrates a higher level of stability and efficiency in most instances, while the CP-II method excels in optimizing line length and station utilization. These results illustrate the potential for optimizing multi-line disassembly systems with optional common stations to enhance production flexibility in remanufacturing processes.& COPY;2023 Elsevier Inc. All rights reserved.

关键词： multiple objective programming Mixed-integer programming Constraint programming Disassembly line balancing Parallel disassembly lines

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Ordinal optimization through multi-objective reformulation

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第2期311卷 427-443页

作者： Klamroth, Kathrin Stiglmayr, Michael Sudhoff, Julia Univ Wuppertal Sch Math & Nat Sci IMACM Gaussstr 20 D-42119 Wuppertal Germany

We analyze combinatorial optimization problems with ordinal, i.e., non-additive, objective functions that assign categories (like good, medium and bad) rather than cost coefficients to the elements of feasible so-lutions. We review different optimality concepts for ordinal optimization problems and discuss their sim-ilarities and differences. We then focus on two prevalent optimality concepts that are shown to be equiv-alent. Our main focus lies on the investigation of a bijective linear transformation that transforms ordinal optimization problems to associated standard multi-objective optimization problems with binary cost co-efficients. Since this transformation preserves all properties of the underlying problem, problem-specific solution methods remain applicable. A prominent example is dynamic programming and Bellman's prin-ciple of optimality, that can be applied, e.g., to ordinal shortest path and ordinal knapsack problems. We investigate the interrelation between scalarization techniques and methods based on the hypervolume indicator when applied to the ordinal and the transformed problem, respectively. Furthermore, we ex-tend our results to multi-objective optimization problems that combine ordinal and real-valued objective functions.& COPY;2023 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Ordering cones Ordinal objective functions Combinatorial optimization

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Efficient multi-objective optimization through parallel surrogate-assisted local search with tabu mechanism and asynchronous option

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ENGINEERING OPTIMIZATION 2024年第7期56卷 1081-1097页

作者： Wang, Wenyu Akhtar, Taimoor Shoemaker, Christine A. Natl Univ Singapore Dept Ind Syst Engn & Management Singapore Singapore Univ Guelph Sch Engn Guelph ON Canada

Multi-objective optimization is challenging for computationally expensive objectives because most optimization methods rely on a large number of function evaluations to approach the Pareto-optimal front. To this end, this article develops a novel multi-objective optimization algorithm, the Multi-objective Parallel Local Surrogate-assisted search (MOPLS) algorithm, which combines surrogate approximation and parallel computing. In each iteration, MOPLS incorporates a tabu mechanism to determine new points for expensive evaluations via a series of independent surrogate-assisted local searches. A master-worker architecture in MOPLS allows the algorithm to conduct either synchronous or asynchronous parallel processing. On a number of benchmark problems, MOPLS outperforms recent surrogate-assisted algorithms within a limited computational budget. Empirical results from parallel experiments indicate that MOPLS can significantly improve its efficiency through parallelism, and the asynchronous MOPLS shows advantages in handling objectives with non-constant evaluation times. Finally, the better performance of MOPLS over alternatives in calibrating a complex watershed simulation model demonstrates its competitiveness in solving real-world engineering applications.

关键词： multiple objective programming expensive objectives radial basis functions tabu list asynchronous parallel processing

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Advancements in the computation of enclosures for multi-objective optimization problems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期310卷 315-327页

作者： Eichfelder, Gabriele Warnow, Leo Tech Univ Ilmenau Inst Math PO 10 05 65 D-98684 Ilmenau Germany

A central goal for multi-objective optimization problems is to compute their nondominated sets. In most cases these sets consist of infinitely many points and it is not a practical approach to compute them exactly. One solution to overcome this problem is to compute an enclosure, a special kind of coverage, of the nondominated set. For that computation one often makes use of so-called local upper bounds. In this paper we present a generalization of this concept. For the first time, this allows to apply a warm start strategy to the computation of an enclosure. We also show how this generalized concept allows to remove empty areas of an enclosure by deleting certain parts of the lower and upper bound sets which has not been possible in the past. We demonstrate how to apply our ideas to the box approximation algorithm, a general framework to compute an enclosure, as recently used in the solver called BAMOP. We show how that framework can be simplified and improved significantly, especially concerning its practical numerical use. In fact, we show for selected numerical instances that our new approach is up to eight times faster than the original one. Hence, our new framework is not only of theoretical but also of practical use, for instance for continuous convex or mixed-integer quadratic optimization problems.(c) 2023 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Nonlinear programming Mixed -integer programming Enclosure Warm start strategies

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Two-phase strategies for the bi-objective minimum spanning tree problem

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2022年第6期29卷 3435-3463页

作者： Amorosi, Lavinia Puerto, Justo Sapienza Univ Rome Dept Stat Sci Ple Aldo Moro 5 I-00185 Rome Italy Univ Seville Dept Stat Sci & Operat Res Seville Spain

This paper presents a new two-phase algorithm for the bi-objective minimum spanning tree (BMST) problem. In the first phase, it computes the extreme supported efficient solutions resorting to both mathematical programming and algorithmic approaches, while the second phase is devoted to obtaining the remaining efficient solutions (non-extreme supported and non-supported). This latter phase is based on a new recursive procedure capable of generating all the spanning trees of a connected graph through edge interchanges based on increasing evaluation of non-zero reduced costs of associated weighted linear programs. Such a procedure exploits a common property of a wider class of problems to which the minimum spanning tree (MST) problem belongs, that is the spanning tree structure of its basic feasible solutions. Computational experiments are conducted on different families of graphs and with different types of cost. These results show that this new two-phase algorithm is correct, very easy to implement and it allows one to extract conclusions on the difficulty of finding the entire set of Pareto solutions of the BMST problem depending on the graph topology and the possible correlation of the edge costs.

关键词： multiple objective programming combinatorial optimisation minimum spanning tree two-phase methods

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