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Meta-heuristic algorithm for aircraft pre-tactical conflict resolution with altitude and heading angle change maneuvers

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TOP 2021年第3期29卷 629-647页

作者： Cecen, Ramazan Kursat Sarac, Tugba Cetek, Cem Eskisehir Osmangazi Univ Eskisehir Turkey Eskisehir Tech Univ Eskisehir Turkey

Aircraft conflict resolution is of great importance for the safe and efficient management of air traffic. This study proposes a two-step optimization approach for the aircraft conflict resolution problems within the pre-tactical time window in generic free route airspace. Safe separation between aircraft pairs is maintained using either altitude or heading angle change maneuvers in a pre-defined buffer zone within the boundaries of the airspace. The first step of the model aims to minimize the total number of conflicting aircraft and the total fuel consumption together using altitude change maneuvers. A mixed-integer linear programming model is proposed for the first step but, due to the high computational time, a metaheuristic algorithm (simulated annealing) was developed. If the altitude change does not resolve all conflicts in the first step, the proposed model implements heading angle change maneuvers with minimum extra fuel burn in the second step. A nonlinear programming model is presented for the second step. Numerical results show that the proposed approach can resolve all conflicts in less than 4 min for the highest traffic flow rate.

关键词： Aircraft conflict resolution Air traffic management Meta-heuristic algorithm Non-linear programming model mixed-integer linear programming model Free route airspace

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A Genetic algorithm scheme for large scale open-pit mine production scheduling

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MINING TECHNOLOGY-TRANSACTIONS OF THE INSTITUTIONS OF MINING AND METALLURGY 2023年第4期132卷 225-236页

作者： Azadi, Nooshin Mirzaei-Nasirabad, Hossein Mousavi, Amin Sahand Univ Technol Fac Min Engn Tabriz Iran Tarbiat Modares Univ Fac Min Engn Tehran Iran Sahand Univ Technol Tabriz Iran

Due to the large size of open-pit mines' long-term production scheduling (OPMPS) problem in large-scale deposits, it is challenging to solve that problem as the mixed integer linear programming (MILP) model. This study used an approach of the genetic algorithm (GA) to tackle this challenge. So, in a small hypothetical deposit, based on the blocks in the ultimate pit limit and scenarios with 2-6 phases, net present values (NPV) and computational times obtained from the GA and MILP model were compared to evaluate the GA. Also, the GA was applied to a large-scale deposit to determine the efficiency of the GA in real deposits. The maximum NPV was obtained for the four-phase scenario in the hypothetical deposit and the six-phase scenario in the large-scale deposit. Although the GA's NPV decreased slightly compared to the global optimum solution from the MILP model, the computational time was significantly reduced.

关键词： Open-Pit mine ultimate pit limit net present value operational constraints NP-hard problem long-term production scheduling genetic algorithm mixed-integer linear programming model

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Fix-and-optimize procedures for solving the long-term unit commitment problem with pumped storages

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ANNALS OF OPERATIONS RESEARCH 2019年第1-2期274卷 241-265页

作者： Franz, Alexander Rieck, Julia Zimmermann, Juergen Tech Univ Clausthal Inst Management & Econ Operat Res Grp D-38678 Clausthal Zellerfeld Germany Univ Hildesheim Inst Econ & Comp Sci Operat Res Grp D-31141 Hildesheim Germany

In this paper, we consider a long-term unit commitment problem with thermal and renewable energy sources, where system operating costs have to be minimized. The problem is enhanced by adding pumped storages, where water is stored in reservoirs, being turbinated or pumped up if it is beneficial in terms of reducing the operating costs. We present a tight mixed-integer linear programming model with a redefinition of decision variables and a reformulation of constraints, e.g., for the spinning reserve. The model serves as a basis for a new decomposition method, where fix-and-optimize schemes are used. In particular, a time-oriented, a unit-oriented, and a generic fix-and-optimize procedure are presented. A computational performance analysis shows that the mixed-integer linear model is efficient in supporting the solution process for small- and medium-scale instances. Furthermore, the fix-and-optimize procedures are able to tackle even large-scale instances. Particularly, problem instances with real-world energy demands, power plant-specific characteristics, and a one-year planning horizon with hourly time steps are solved to near-optimality in reasonable time.

关键词： Unit commitment problem Pumped storages Hydrothermal coordination Volatile residual demand patterns mixed-integer linear programming model Fix-and-optimize procedure

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Warm-start piecewise linear approximation-based solution for load pick-up problem in electrical distribution system

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IET SMART GRID 2020年第3期3卷 385-393页

作者： Yun, Jingyang Hu, Weidong Zhou, Yun Yan, Zheng Feng, Donghan Li, Naihu Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China Minist Educ Key Lab Control Power Transmiss & Convers SJTU Shanghai Peoples R China Chint Grp Shanghai Peoples R China

As the core sub-problem of both network reconfiguration and service restoration of the electrical distribution system (EDS), the load pick-up (LPP) problem in EDS searches the optimal configuration of the EDS, aiming to minimise the power loss or provide as much power as possible to load ends. The piecewise linearisation (PWL) approximation method can be used to tackle the network power flow constraints' non-linearity in the LPP problem model, and transform the LPP model into a mixed-integer linear programming model (LPP-MILP model). The errors in the PWL approximation of the network power flow constraints may affect the feasibility of the solving results of the LPP-MILP model. The single method to reduce the PWL approximation errors by increasing the number of discretisations in PWL function is not stable. Moreover, the solution efficiency of the LPP-MILP model is sacrificed severely. In this study, a warm-start PWL approximation-based solution for the LPP problem is proposed. The variable upper bounds in the PWL approximation functions are renewed dynamically in the warm-start solution procedure to reduce the PWL approximation errors with higher computational efficiency. Modified IEEE 33-bus radial distribution test system and a real and large distribution system, 1066-bus system, are used to test and verify the effectiveness and robustness of the proposed methodology.

关键词： linear programming load flow integer programming piecewise linear techniques approximation theory distributed power generation power loss piecewise linearisation approximation method network power flow constraints LPP problem model LPP model mixed-integer linear programming model LPP-MILP model PWL approximation errors PWL function PWL approximation-based solution PWL approximation functions radial distribution test system warm-start piecewise linear approximation-based solution load pick-up problem electrical distribution system core sub-problem network reconfiguration service restoration EDS

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Plant co-ordination in pharmaceutics supply networks

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OR SPECTRUM 2003年第1期25卷 109-141页

作者： Grunow, M Günther, HO Yang, G Tech Univ Berlin Dept Prod Management D-10585 Berlin Germany

The production of active ingredients in the chemical-pharmaceutical industry involves numerous production stages with cumulative lead times of up to two years. Mainly because of rigorous purity requirements and the need of extensive cleaning of the equipment units, production is carried out in campaigns, i.e. multiple batches of the same product type are produced successively before changing to another product type. Each campaign requires a specific configuration of equipment units according to the recipes of the particular chemical process. In the chemicalpharmaceutical industry, production stages are often assigned to different locations, even different countries. Hence the co-ordination of plant operations within the resulting multi-national supply network is of major importance. A key issue is the co-ordination of campaign schedules at different production stages in the various plants. In practice, it is almost impossible to determine exact optimal solutions to the corresponding complex supply network problem with respect to overall logistics costs. In order to reduce the required computational effort, we introduce several aggregation schemes and a novel MILP model formulation which is based on a continuous representation of time. Moreover, we propose an iterative near-optimal solution procedure which can be successfully applied to even exceptionally large real life problem instances. The applicability of the approach suggested is shown using a case study from industry.

关键词： supply network planning pharmaceutical industry mixed-integer linear programming model aggregation techniques hierarchical production planning

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Vehicle routing problem under safe separation distance for multiple unmanned aerial vehicle operation

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OPERATIONAL RESEARCH 2022年第5期22卷 5107-5136页

作者： Uhm, Hyun Seop Lee, Young Hoon Yonsei Univ Dept Ind Engn 50 Yonsei Ro Seoul 03722 South Korea

In this work, we present a variant of the vehicle routing problem for multiple unmanned aerial vehicle operation. The problem was described as a multi-depot vehicle routing problem with separation distance constraints, and two mathematical models were developed to find the best routes under capacity, maximum traveling time, and intervehicle separation constraints. In the first model, the separation distance constraint was proposed using a discrete time window based on previous studies, while the second model restricts the relative difference of departure time between every two arcs within the safety distance. Although the second model was designed using the mixed-integer linear programming model, finding acceptable solutions within a limited computation time was a challenge. Therefore, a decomposition heuristic, which divides the second model into a routing step followed by a scheduling step, and a hybrid tabu search algorithm with constructive initial solution generation were suggested. The performance of the suggested algorithms was evaluated for randomly generated graphs in two-dimensional space, and computational experiments showed that the proposed algorithms can be applied to practical cases with enhanced computational efficiency.

关键词： Multi-depot vehicle routing problem Intervehicle separation distance Departure time scheduling mixed-integer linear programming model Decomposition heuristic Hybrid initial solution generation Tabu search heuristic

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A method for designing centralized emergency supply to respond to large-scale natural disasters

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2014年 67卷 284-305页

作者： Sheu, Jiuh-Biing Pan, Cheng Natl Taiwan Univ Dept Business Adm Taipei 106 Taiwan

This paper proposes a method for designing a seamless centralized emergency supply network by integrating three sub-networks (shelter network, medical network, and distribution network) to support emergency logistics operations in response to large-scale natural disasters. The proposed method primarily involves three stage multi-objective (travel distance minimization, operational cost minimization, and psychological cost minimization), mixed-integer linear programming models. The three sub-networks are designed using the proposed programming models. The distinctive features of the proposed method are as follows. (1) The proposed method is demand-driven. The order of the designed sub-networks is shelter, medical, and distribution, with the connections of the latter networks based on the arrangements for the former. (2) The objective functions of three stage programming models include not only traditional objectives such as minimizing total travel distance and operational cost, which supply-side members focus on, but also minimizing the psychological cost experienced by demand-side members. model tests are conducted to demonstrate that the superiority of a centralized emergency supply network designed by the proposed method over a decentralized one, especially with regard to distribution network design. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Centralized emergency supply network Emergency logistics mixed-integer linear programming model

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modeling and solution methods for hybrid flow shop scheduling problem with job rejection

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OPERATIONAL RESEARCH 2022年第3期22卷 2721-2765页

作者： Dabiri, Mohamadreza Yazdani, Mehdi Naderi, Bahman Haleh, Hassan Islamic Azad Univ Dept Ind Engn Fac Ind & Mech Engn Qazvin Branch Qazvin Iran Univ Windsor Dept Mech Automot & Mat Engn Fac Engn Windsor ON Canada Golpayegan Univ Technol Dept Ind Engn Golpayegan Iran

This paper addresses the hybrid flow shop scheduling problem by considering job rejection to minimize the sum of the total tardiness cost of the scheduled jobs and total cost of the rejected jobs as a single-objective problem. A mixed-integer linear programming model is proposed to solve small-sized problems within an acceptable computational time. Also, this paper exhibits two innovative heuristic algorithms, which are presented to discover fast solutions for the problem along with five meta-heuristics are adapted to solve large-sized problems in the model. Another contribution of this paper is to illustrate the different encoding and decoding methods adapted to algorithms, which are capable of obtaining a feasible schedule and furthermore, to guarantee the efficiency of the solutions based on the schedule. The results obtained from the computational study demonstrate the mathematical model and proposed algorithms effectiveness. Additionally, this paper studies the efficacy of job rejection noting the scheduling for a real-world hybrid flow shop in the tile industry production system. As well as, in this paper, the problem is viewed from a bi-objective problem perspective, so that the tardiness costs of the scheduled jobs and rejection costs of rejected jobs as two objectives are minimized simultaneously to obtain the Pareto solutions. We analyze relationship between the results of the single-objective and bi-objective approaches on small and large-sized problems.

关键词： Scheduling Hybrid flow shop mixed-integer linear programming model Meta-heuristic algorithm Heuristic algorithm

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A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries

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ANNALS OF OPERATIONS RESEARCH 2021年 1-34页

作者： Tavana, Madjid Govindan, Kannan Nasr, Arash Khalili Heidary, Mohammad Saeed Mina, Hassan La Salle Univ Business Syst & Analyt Dept Distinguished Chair Business Analyt Philadelphia PA 19141 USA Univ Paderborn Fac Business Adm & Econ Business Informat Syst Dept D-33098 Paderborn Germany Univ Southern Denmark Dept Technol & Innovat Odense Denmark Sharif Univ Technol Grad Sch Management & Econ Tehran Iran Allameh Tabatabai Univ Fac Management & Accounting Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran

Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the heterogeneous population are among the practical assumptions in the proposed approach. Real-world data is used to demonstrate the efficiency and effectiveness of the mathematical programming approach proposed in this study.

关键词： Vaccine supply chain Coronavirus vaccine Equitable distribution Location-inventory problem mixed-integer linear programming model COVID-19

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A bi-objective network design model for multi-period, multi-product closed-loop supply chain

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2013年第4期30卷 264-280页

作者： Pazhani, Subramanian Ramkumar, N. Narendran, T. T. Ganesh, K. Penn State Univ Harold & Inge Marcus Dept Ind & Mfg Engn University Pk PA 16802 USA JDA Software India Pvt Ltd Logist Div Hyderabad 500081 Andhra Pradesh India Indian Inst Technol Madras Dept Management Studies Madras 600036 Tamil Nadu India McKinsey & Co Inc McKinsey Knowledge Ctr India Private Ltd Supply Chain Management Ctr Competence Gurgaon 122011 Haryana India

Concerns over environmental degradation legislative requirements and growing business needs have fueled the growth of closed-loop supply chains (CLSCs). This paper addresses a bi-objective network design problem for multi-period, multi-product CLSC to minimize the total supply chain costs and to maximize the service efficiency of the warehouses and hybrid facilities. We develop a bi-objective mixed integer linear programming model to assist decisions in (1) location/operating decisions for warehouses, hybrid facilities and manufacturing facilities and (2) production and distribution of products between stages in the supply chain. Goal programming models and compromise programming techniques are used to solve the problem. An application of the model is demonstrated using a case study from the literature.

关键词： closed-loop supply chain mixed-integer linear programming model goal programming compromise programming

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