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A two-stage approach for bi-objective integer linear programming

OPERATIONS RESEARCH LETTERS 2018年第1期46卷 81-87页

作者： Dai, Rui Charkhgard, Hadi Univ S Florida Dept Ind & Management Syst Engn Tampa FL 33620 USA

We present a new exact approach for solving bi-objective integer linear programs. The new approach employs two of the existing exact algorithms in the literature, including the balanced box and the is an element of-constraint methods, in two stages. A computationally study shows that the new approach has three desirable characteristics. (1) It solves less single-objective integer linear programs. (2) Its solution time is significantly smaller. (3) It is competitive with the two-stage algorithm proposed by Leitner et al. (2016). (C) 2017 Elsevier B.V. All rights reserved.

关键词： Two-stage approach Balanced box method is an element of-constraint method bi-objective integer linear programming

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A Feasibility Pump and Local Search Based Heuristic for bi-Obiective Pure integer linear programming

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INFORMS JOURNAL ON COMPUTING 2019年第1期31卷 115-133页

作者： Pal, Aritra Charkhgard, Hadi Univ S Florida Dept Ind & Management Syst Tampa FL 33620 USA

We present a new heuristic algorithm to approximately generate the nondominated frontier of bi-objective pure integer linear programs. The proposed algorithm employs a customized version of several existing algorithms in the literature of both single-objective and bi-objective optimization. Our proposed method has two desirable characteristics: (1) there is no parameter to be tuned by users other than the time limit;(2) it can naturally exploit parallelism. An extensive computational study shows the efficacy of the proposed method on some existing standard test instances in which the true frontier is known, and also some large randomly generated instances. We show that even a basic version of our algorithm can significantly outperform the Nondominated Sorting Genetic Algorithm II (Deb et al. 2002), and the sophisticated version of our algorithm is competitive with Multidirectional Local Search (Tricoire 2012). We also show the value of parallelization on the proposed approach.

关键词： bi-objective integer linear programming feasibility pump local search perpendicular search method parallelization

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bi-objective autonomous vehicle repositioning problem with travel time uncertainty

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4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2020年第4期18卷 477-505页

作者： Charkhgard, Hadi Takalloo, Mahdi Haider, Zulqarnain Univ S Florida Dept Ind & Management Syst Engn Tampa FL 33620 USA

We study the problem of repositioning autonomous vehicles in a shared mobility system in order to simultaneously minimize the unsatisfied demand and the total operating cost. We first present a mixed integer linear programming formulation for the deterministic version of the problem. We extend this formulation to make it easier to work with in the non-deterministic setting. We then show how the travel time uncertainty can be incorporated into this extended deterministic formulation using chance-constraint programming. Finally, two new reformulations for the proposed chance-constraint program are developed. We show a critical result that the size of one of the reformulations (in terms of the number of variables and constraints) does not depend on the number of scenarios, and so it outperforms the other reformulation. Both reformulations are bi-objective mixed integer linear programs with a finite number of nondominated points and so they can be solved directly by algorithms such as the balanced box method (Boland et al. in INFORMS J Comput 27(4):735-754, 2015). A computational study demonstrates the efficacy of the proposed reformulations.

关键词： Autonomous vehicle repositioning problem bi-objective integer linear programming Chanced-constraint programming

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bi-objective integer programming of Hospitals Under Dynamic Electricity Price 10th

Bi-Objective Integer Programming of Hospitals Under Dynamic ...

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10th International Conference on Management Science and Engineering Management (ICMSEM)

作者： Vaziri, Shabnam Mahmoudzadeh Rezaee, Babak Monirian, Masoud Amel Ferdowsi Univ Mashhad Ind Engn Dept Fac Engn Mashhad Iran

ISBN: (纸本)9789811018374;9789811018367

In response to rising costs of health services and competitive environment, health care organizations have to provide high quality services at lowest possible costs. On the other hand, energy prices are increasing due to the depletion of fossil fuel sources which cause an increment in health centers costs. Given these considerations, it is essential to find ways to use energy more efficiently. This paper presents a novel model for energy management in hospitals as a non-isolated micro grid that is connected to the main grid by the distribution transmission lines. Minimizing the energy costs (considering revenue, renewable energy subsidies and overtime costs) and minimizing the displeasure of surgeons and patients will be the target. We develop bi-objective integer linear programming model for this problem. It's assumed that the hospital can buy its power shortage from the main grid and is also able to sell the extra energy produced to the electricity market. It is also considered that the cost of purchasing energy from the grid is determined based on the hourly market prices of electricity.

关键词： Health centers Energy use bi-objective integer linear programming

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Providing an integrated Model for Planning and Scheduling Energy Hubs and preventive maintenance

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ENERGY 2018年 163卷 1093-1114页

作者： Amiri, S. Honarvar, M. Sadegheih, A. Yazd Univ Dept Ind Engn Yazd Iran

In this paper, a bi-objective mathematical model is presented for energy hub scheduling with consideration of preventive maintenance policy. In the model, the hub equipment is assumed to be at risk of random failure, and a periodic preventive maintenance action is planned considering the energy hub utilization plan to take the system into an operational state as good as new. The aim of the proposed model is to determine the preventive maintenance cycles and the best strategy to allocate hub energy capacity under different demand scenarios, while the goals are to minimize costs and to maximize the reliability of the system. The novelty of this paper is the integration of preventive maintenance scheduling and energy hub scheduling. Considering the uncertainty of the demand, a scenario-based two stage stochastic programming approach is used. CPLEX solver of GAMS is used to solve the model based on the Epsilon-constraint method. The sensitivity analysis is provided to define the effect of parameters such as demand and capacity on the model. The performance of the proposed integrated model is compared with the solutions offered by two well-known techniques from the subject literature. The results show that the integrated model possesses outstanding performance. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Energy hub Preventive maintenance bi-objective integer linear programming Epsilon constraint

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Solving the bi-objective integer programming: A DEA Methodology

Solving the Bi-Objective Integer Programming: A DEA Methodol...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Keshavarz, Esmaiel Toloo, Mehdi Islamic Azad Univ Cent Tehran Branch Dept Math Tehran Iran Tech Univ Ostrava Fac Econ Ostrava Czech Republic

ISBN: (纸本)9781479967735

Finding and classifying all efficient solutions for a bi-objective integer linear programming (BOILP) problem is one of the controversial issues in Multi-Criteria Decision Making problems. The main aim of this study is to utilize the well-known Data Envelopment Analysis (DEA) methodology to tackle this issue. Toward this end, we first state some propositions to clarify the relationships between the efficient solutions of a BOILP and efficient Decision Making Units (DMUs) in DEA and next design a new two-stage approach to find and classify a set of efficient solutions. Stage I formulates a two-phase Mixed integer linear programming (MILP) model, based on the Free Disposal Hull (FDH) model in DEA, to gain a Minimal Complete Set of efficient solutions. Stage II uses a variable returns to scale DEA model to classify the obtained efficient solutions from Stage I as supported and non-supported. A BOILP model containing 6 integer variables and 4 constraints is solved as an example to illustrate the applicability of the proposed approach.

关键词： bi-objective integer linear programming Data Envelopment Analysis Efficient solution Supported efficient solution Non-dominated point

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