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Optimizing the ground intra-city express delivery network: An integrated multiple centrality assessment, multi-criteria decision-making, and multi-objective integer programming model

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JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 2024年第4期28卷 525-543页

作者： Liu, Chuang Zhou, Jianjun Gan, Junwei Wu, Yuexin Huang, Yulong Shao, Jiahao Ouyang, Lingyi Chengdu Vocat & Tech Coll Ind Sch Finance & Business Chengdu Sichuan Peoples R China Sichuan Univ Business Sch Chengdu Sichuan Peoples R China Sichuan Tourism Univ Sch Econ & Management Chengdu Sichuan Peoples R China Haikou Univ Econ Dept Gen Educ Foreign Languages Haikou Hainan Peoples R China Sichuan Tourism Univ Sch Econ & Management Chengdu 610100 Sichuan Peoples R China

Optimization of an intra-city express delivery network from three to two levels is of great interest to suppliers and customers for reducing costs and improving service efficiency. One feasible solution is to identify critical nodes in the three-level network and upgrade them as transshipment facilities in the two-level one. However, traditional optimization models seldom combine empirical business data, composite metrics, and objective evaluation rules. We proposed an approach integrating empirical data, multi-criteria decision-making methods based on the real-world application of the SF Express Chengdu branch. We also developed a mathematical optimization model using statistical and operations management techniques combined with logistics expertise for a location decision. First, the appropriateness of each service point as a candidate transshipment facility is evaluated from internal and external perspectives by applying multiple centrality assessment from complex network theory and fuzzy Technique for Order Preference by Similarity to an Ideal Solution, respectively. Second, 16 candidate transshipment facilities are selected by combining these two ways. Then, a multi-objective integer programming model is built to obtain the optimal number, locations of transshipment facilities, and the corresponding service points covered by each transshipment facility. Using this multi-methodologic approach, we show that the optimized two-level network is economically feasible and simply applicable, with the total cost and average delivery time reduced by 18.41% and 6 h, respectively. This article is of practical significance and provides an important reference for optimizing ground express service networks for other large cities.

关键词： Fuzzy TOPSIS ground intra-city express delivery network multi-objective integer programming multiple centrality assessment optimization

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multi-objective integer programming Approaches for Solving the multi-criteria Test-suite Minimization Problem: Towards Sound and Complete Solutions of a Particular Search-based Software-engineering Problem

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ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2020年第3期29卷 20-20页

作者： Xue, Yinxing Li, Yan-Fu Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Anhui Peoples R China Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China

Test-suite minimization is one key technique for optimizing the software testing process. Due to the need to balance multiple factors, multi-criteria test-suite minimization (MCTSM) becomes a popular research topic in the recent decade. The MCTSM problem is typically modeled as integer linear programming (ILP) problem and solved with weighted-sum single objective approach. However, there is no existing approach that can generate sound (i.e., being Pareto-optimal) and complete (i.e., covering the entire Pareto front) Pareto-optimal solution set, to the knowledge of the authors. In this work, we first prove that the ILP formulation can accurately model the MCTSM problem and then propose the multi-objective integer programming (MOIP) approaches to solve it. We apply our MOIP approaches on three specific MCTSM problems and compare the results with those of the cutting-edge methods, namely, Nonlinearformulation_LinearSolver (NF_LS) and two multi-objective Evolutionary Algorithms (MOEAs). The results show that our MOIP approaches can always find sound and complete solutions on five subject programs, using similar or significantly less time than NF_LS and two MOEAs do. The current experimental results are quite promising, and our approaches have the potential to be applied for other similar search-based software engineering problems.

关键词： Regression testing search-based software engineering test-suite minimization multi-objective integer programming big-M method epsilon-constraint method CWMOIP

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A New Gateway Selection Algorithm Based on multi-objective integer programming and Reinforcement Learning

INFOCOMMUNICATIONS JOURNAL

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INFOCOMMUNICATIONS JOURNAL 2022年第4期14卷 4-10页

作者： Alabbas, Hasanain Huszak, Arpad Budapest Univ Technol & Econ Fac Elect Engn & Informat Dept Networked Syst & Serv Budapest Hungary Al Qasim Green Univ Comp Ctr Dept Al Qasim Iraq ELKH BME Cloud Applicat Res Grp Budapest Hungary

Connecting vehicles to the infrastructure and benefiting from the services provided by the network is one of the main objectives to increase safety and provide well-being for passengers. Providing such services requires finding suitable gateways to connect the source vehicles to the infrastructure. The major of applications with high bandwidth demand that can cause network congestion, particularly in urban areas with a highdensity vehicle. This work introduces a novel gateway selection algorithm for vehicular networks in urban areas, consisting of two phases. The first phase identifies the best gateways among the deployed vehicles using multi-objective integer programming. While in the second phase, reinforcement learning is employed to select a suitable gateway for any vehicular node in need to access the VANET infrastructure. The proposed model is evaluated and compared to other existing solutions. The obtained results show the efficiency of the proposed system in identifying and selecting the gateways.

关键词： VANET gateway selection multi-objective integer programming reinforcement learning

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Decision space robustness for multi-objective integer linear programming

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ANNALS OF OPERATIONS RESEARCH 2022年第2期319卷 1769-1791页

作者： Stiglmayr, Michael Figueira, Jose Rui Klamroth, Kathrin Paquete, Luis Schulze, Britta Univ Wuppertal Sch Math & Nat Sci Wuppertal Germany Univ Lisbon Inst Super Tecn CEG IST Lisbon Portugal Univ Coimbra Dept Informat Engn CISUC Coimbra Portugal

In this article we introduce robustness measures in the context of multi-objective integer linear programming problems. The proposed measures are in line with the concept of decision robustness, which considers the uncertainty with respect to the implementation of a specific solution. An efficient solution is considered to be decision robust if many solutions in its neighborhood are efficient as well. This rather new area of research differs from robustness concepts dealing with imperfect knowledge of data parameters. Our approach implies a two-phase procedure, where in the first phase the set of all efficient solutions is computed, and in the second phase the neighborhood of each one of the solutions is determined. The indicators we propose are based on the knowledge of these neighborhoods. We discuss consistency properties for the indicators, present some numerical evaluations for specific problem classes and show potential fields of application.

关键词： multi-objective integer programming Decision space robustness Connectedness of efficient solutions Representation Decision analysis

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Optimization Production Scheduling of Underground Backfilling Mining Based on NSGA-II

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MINING METALLURGY & EXPLORATION 2022年第4期39卷 1521-1536页

作者： Bao, Yu Wang, Yutao Zhao, Liang Zhang, Aijuan China Univ Min & Technol Dept Comp Sci & Technol Daxue Rd Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Mine Digitizat Engn Res Ctr Minist Educ Peoples Republ China Daxue Rd Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Sch Mine Daxue Rd Xuzhou 221116 Jiangsu Peoples R China

In the green backfilling mining of underground coal mines, gangue in a coal seam is used to replace and fill goafs. However, the gas drainage time changes in the amount of gangue output and order in the extraction sequence of stope blocks, thereby changing the production output. A multi-objective integer programming model was proposed to solve this based on an improved non-dominated sorting genetic algorithm. The results show a feasible gangue filling rate can be found and the extraction sequence for a long-term planning time is optimized. It increases the planned annual output by 26% and reduces equipment idle time.

关键词： Underground mine production scheduling Underground backfilling mine Non-dominated sorting genetic algorithm II (NSGA-II) multi-objective integer programming

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The evaluation of renewable energy resources in Turkey by integer multi-objective selection problem with interval coefficient

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RENEWABLE ENERGY 2022年第0期182卷 842-854页

作者： Karaaslan, Abdulkerim Gezen, Mesliha Ataturk Univ Fac Econ & Adm Sci Erzurum Turkey

This paper aims to provide a scientific approach that indicates the need to focus on renewable energypotential to meet energy needs in Turkey. Turkey began to take advantage of renewable energy tech-nologies a few years ago. Accordingly, the issue of determining the best renewable resources for thecountry has been brought to the agenda in recent years. The issue was considered to be a limited multi-objective optimization problem allowing us to achieve a reliable result. However, the parameter of eachresource was considered as a range value, rather than traditionally expressed as an exact value, and amulti-objective decision problem was developed with an interval coefficient. This method allows us toobtain more accurate and reliable results without the need to resort to normalization methods used toeliminate unit differences. According to the results of this study, the most convenient alternatives forTurkey are hydro, wind, and solar power. Thefindings also support decision policies aimed at reachingtargets for the electricity sector in 2023, as put forth by the Ministry of Energy and Natural Resources(MENR). (c) 2021 Elsevier Ltd. All rights reserved

关键词： Fuzzy programming Interval parameter multi-objective integer programming Renewable energy planning

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An improved algorithm to compute the ω-primality

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OPTIMIZATION LETTERS 2021年第1期15卷 97-107页

作者： Achour, Wissem Chaabane, Djamal Blanco, Victor USTHB Dept Operat Res Algiers Algeria Univ Granada IEMath GR Granada Spain

In this paper, we present an improved methodology to compute the omega-primality of a numerical semigroup. The approach is based on exploiting the structure of the problem on a resolution method for optimizing a linear function over the set of efficient solutions of a multiple objective integer linear programming problem. The numerical experiments show the efficiency of the proposed technique compared to the existing methods.

关键词： Global optimization Numerical semigroups Optimization over an efficient set multi-objective integer programming Omega primality

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A predictive and prescriptive analytical framework for scheduling language medical interpreters

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HEALTH CARE MANAGEMENT SCIENCE 2021年第3期24卷 531-550页

作者： Ahmed, Abdulaziz Frohn, Elizabeth Univ Minnesota Business Dept Crookston MN 56716 USA Cloudbreak Healthath Bloomington MN USA

Although most hospitals in the United States provide medical services in English, a significant percentage of the U.S. population uses languages other than English. Mostly, the interpreting department in a hospital finds interpreters for limited English proficiency (LEP) patients, including inpatients, outpatients, and emergency patients. The department employs full-time and part-time interpreters to cover the demand of LEP patients. Two main challenges are facing an interpreting department: 1) there are many interpreting agencies in the market in which part-time interpreters can be chosen from. Selecting a part-time interpreter with the best service quality and lowest hourly rate makes the scheduling process difficult. 2) the arrival of LEP emergency patients must be predicted to make sure that LEP emergency patients are covered and to avoid any service delay. This paper proposes a framework for scheduling full-time and part-time interpreters for medical centers. Firstly, we develop a prediction model to forecast LEP patient demand in the emergency department (ED). Secondly, we develop a multi-objective integer programming (MOIP) model to assign interpreters to inpatient, outpatient, and emergency LEP patients. The goal is to minimize the total interpreting cost, maximize the quality of the interpreting service, and maximize the utilization of full-time interpreters. Various experiments are conducted to show the robustness and practicality of the proposed framework. The schedules generated by our model are compared with the schedules generated by the interpreting department of a partner hospital. The results show that our model produces better schedules with respect to all three objectives.

关键词： Interpreting service multi-objective integer programming Predictive modeling Prescriptive modeling Healthcare service Scheduling Operations research

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Branch-and-bound and objective branching with three or more objectives

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COMPUTERS & OPERATIONS RESEARCH 2022年 148卷

作者： Forget, Nicolas Gadegaard, Sune Lauth Klamroth, Kathrin Nielsen, Lars Relund Przybylski, Anthony Aarhus Univ Sch Business & Social Sci Dept Econ & Business Econ Fuglesangs Alle 4 DK-8210 Aarhus Denmark Univ Wuppertal Sch Math & Nat Sci Gaussstr 20 D-42119 Wuppertal Germany Univ Nantes Fac Sci & Technol 2 Rue Houssiniere BP 92208 F-44322 Nantes France

The recent success of bi-objective Branch-and-Bound (B&B) algorithms heavily relies on the efficient computa-tion of upper and lower bound sets. These bound sets are used as a supplement to the classical dominance test to improve the computational time by imposing inequalities derived from (partial) dominance in the objective space. This process is called objective branching since it is mostly applied when generating child nodes. In this paper, we extend the concept of objective branching to multi-objective integer optimization problems with three or more objective functions. Several difficulties arise in this case, as there is no longer a lexicographic order among non-dominated outcome vectors when there are three or more objectives. We discuss the general concept of objective branching in any number of dimensions and suggest a merging operation of local upper bounds to avoid the generation of redundant sub-problems. Finally, results from extensive experimental studies on several classes of multi-objective optimization problems is reported.

关键词： multi-objective combinatorial optimization multi-objective integer programming Branch & bound objective branching Bound sets

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Human resource management: new approach to nurse scheduling by considering human error

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2019年第6期10卷 1429-1443页

作者： Nahand, Peyman Kiani Hamidl, Mahdi Bastan, Mahdi Mollajan, Ali Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Univ Eyvanekey Dept Ind Engn Garmsar Iran

Human error is a critical concern in healthcare systems from primary care clinics to operating rooms in hospitals. Prevention or reduction of the chance of occurrence of such errors through increasing human reliabilities is tremendously important and deserves to be focused within personnel scheduling problems in healthcare systems. The present study is to develop a new multi-objective integer mathematical model which includes human errors of nurses to determine optimal shift scheduling of nurses. In addition to medical errors, several constraints in real-world problem including "minimum number of available nurses in each shift", "restrictions on shift rotation for each nurse", and "Minimum and maximum working hours in a week" are also taken into account. Nurses' preference score, allocation costs, penalty cost of violating soft constraints, and human errors are all considered as objectives to be optimized. The multi-objective model, developed in this study, is solved by employing the weighted-sum method. To verify and validate the proposed model, a test problem is also solved. Sensitivity analysis on the model indicates that the solution method can reach acceptable solutions within an acceptable time. The present study is to help decision-makers to achieve optimal scheduling for decreasing costs and improving safety in healthcare systems. Based on this approach, decision makers can totally minimize the number of errors by considering the number of nurses required in each grade as well as proper allocation of them to different work shifts.

关键词： Nurse scheduling multi-objective integer programming Human error Health care

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