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Providing homeland security strategies against interdictions in the city transportation network: A case study in Turkey

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GAZI UNIVERSITY JOURNAL OF SCIENCE 2023年第4期36卷 1601-1623页

作者： Ayyildiz, Ertugrul Ozcelik, Gokhan Gencer, Cevriye Demirci, Emrullah Karadeniz Tech Univ Fac Engn Dept Ind Engn Trabzon Turkiye Gazi Univ Fac Engn Dept Ind Engn Ankara Turkiye

This study defines a capacitated multiple-source multiple-sink shortest path problem and introduces its extension, called the capacitated multiple-source multiple-sink shortest path network interdiction problem (CMSSNIP). CMSSNIP examines the actions of attackers who attempt to maximize the total shortest path of network users trying to reach the crime locations for the aid process after causing an incident in certain regions to provide strategic information for the defense systems of the government. In this context, the exact mathematical model is proposed to ensure useful information about safe routes to network users. In this manner, to the best knowledge of authors, the CMSSNIP consisting of multiple-source nodes and multiple-sink nodes and considering capacity-demand relations between security units and crime locations is studied for the first time. Consequently, a set of scenarios is considered based on the levels of the interdiction budget and the number of crime locations through a real case application to show the applicability of the model. Furthermore, computational experiments are performed to evaluate the performance of the model in networks of different sizes. It is realized that the model provides resilient strategies against interdictions in terms of obtaining the safe shortest paths at the operational level within seconds in the real case applications.

关键词： Shortest path problem Network interdiction mixed integer programming Networks

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Optimising a mathematical model for a multi-sized public bicycle sharing system considering built-in control centres under fuzzy demand, a case study

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS 2023年第1期10卷 Article: 2004259页

作者： Ahangar, Shahin Sadeghi Heidari, Majid Aghsami, Amir Jolai, Fariborz Univ Tehran Coll Engn Sch Ind & Syst Engn POB 11155-4563 Tehran Iran KN Toosi Univ Technol KNTU Sch Ind Engn POB 15875-4416 Tehran Iran

A public bicycle sharing system makes bikes available for users to travel from one station to another in a city. Bicycles are repaired after getting used by users at the control centres if needed and then returned to their source bike station. There are very essential decision criteria to build a bicycle sharing system, the most important of which are the exact number and location of bike stations and control centres, the number of bicycles, and the number of docks in each station. This paper presents a single-objective nonlinear mathematical model for the bicycle sharing problem to minimise the system's total cost considering built-in control centres. Subjective distance is mentioned in this article so that distance-dependent costs become closer to real urban conditions. In this article, two exact and - heuristic methods are considered for solving the problem. Also, the applicability of the proposed model is examined through a real case study. After validating the model in a small dimension, the model is solved by a grasshopper optimisation algorithm in a large scale, and different numerical tests are developed.

关键词： Bicycle sharing systems facility location problem public transportation optimization mixed integer programming fuzzy programming grasshopper optimisation algorithm

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Solving a Two-Level Location Problem with Nonlinear Costs and Limited Capacity: Application of Two-Phase Recursive Algorithm Based on Scatter Search

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FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2023年第3期48卷 371-384页

作者： Meirawan, Danny Ahmed, Alim Al-Ayub Alazzawi, Fouad Jameel Ibrahim Chetthamrongchai, Paitoon Alkhayyat, Ahmed Utami, Ermi Artemova, Elena Igorevna Bykanova, Olga Kurniady, Dedy Achmad Komariah, Aan Univ Pendidikan Indonesia Educ Adm Program Bandung Indonesia Jiujiang Univ Sch Accounting 551 Qianjindonglu Jiujiang Jiangxi Peoples R China AL Rafidain Univ Coll Comp Commun Engn Dept Baghdad Iraq Kasetsart Univ Fac Business Adm Bangkok Thailand Islamic Univ Coll Tech Engn Najaf Iraq Univ Muhammadiyah Kalimantan Timur Fac Econ Business & Polit Dept Management Samarinda 75124 Indonesia Kuban State Agrarian Univ Dept Econ Theory Kalinina St 13 Krasnodar 350044 Russia Plekhanov Russian Univ Econ Dept Higher Math Stremyanny Lane 36 Moscow 117997 Russia

This study examines the issue of distribution network design in the supply chain system. There are many production factories and distribution warehouses in this issue. The most efficient strategy for distributing the product from the factory to the warehouse and from the warehouse to the customer is determined by solving this model. This model combines location problems with and without capacity limits to study a particular location problem. In this system, the cost of production and maintenance of the product in the factory and warehouse is a function of its output. This increases capacity without additional costs, and ultimately does not lose customers. This algorithm is a population-based, innovative method that systematically combines answers to obtain the most accurate answer considering quality and diversity. A two-phase recursive algorithm based on a scattered object has been developed to solve this model. Numerical results show the efficiency and effectiveness of this two-phase algorithm for problems of different sizes.

关键词： mixed integer programming nonlinear costs scattered search algorithm two-tier location

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Integrated Dynamic Cellular Manufacturing Systems and Hierarchical Production Planning with Worker Assignment and Stochastic Demand

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INTERNATIONAL JOURNAL OF ENGINEERING 2023年第2期36卷 348-359页

作者： Bakhshi-Khaniki, H. Ghomi, S. M. T. Fatemi Amirkabir Univ Technol Dept Ind Engn 424 Hafez Ave Tehran Iran

This study deals with the interaction of dynamic cellular manufacturing (DCM) and hierarchical production planning (HPP) problems with stochastic demands for the first time. Each of these alone does not consider the system factors such as stochastic demands and dynamic cellular formation separately. Accordingly, to fill this gap, this paper presents an integrated optimized model incorporating the most comprehensive design of DCM systems and HPP problems with stochastic demands. This model helps administrators get the optimal size and number of cells to decrease costs. Also, the model applies the principles of HPP to reduce the complexity of the integrated model. Since demands are uncertain, they need to be accurately predicted. Therefore, this study aims to combine the most precise decision variables with the most realistic conditions. A case study from an agriculture mechanization and industrial development company shows that an integrated model can provide managers with a feasible solution to meet demand, reconfigure cells in each period, provide new machinery to increase the required production capacity, and adjust production capacity to help them cope with demand fluctuations. A sensitivity analysis was performed and the results show that increase in forecast error and inter-cell move cost cause less significant changes in total cost but the total cost is sensitive to intra-cell move cost, available time capacities and cell quantity. It is also shown that the total cost was very sensitive to available regular time and available over time and the system should try to increase the time capacity.

关键词： Stochastic Demand Hierarchical Production Planning Worker Assignment Cellular mixed integer programming Multi-period Cellular Manufacturing

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An integrated control method for designing non-blocking supervisors using Petri nets

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ADVANCES IN MECHANICAL ENGINEERING 2017年第6期9卷 1-17页

作者： Zhao, Mi Shihezi Univ Coll Machinery & Elect Engn Shihezi 832003 Xinjiang Peoples R China

This article presents an efficient integrated approach on designing a non-blocking supervisor for the most general classes of Petri nets, called G-systems that allow multiple resource acquisitions. This work mainly focuses on developing a deadlock prevention policy with a polynomial computational complexity. First, an extraction algorithm of liveness requirement constraints is presented according to the concept of resource partial orders. By considering the different resource requirements of various processes, monitors are added for the uncontrolled G-system on the basis of those precise linear inequality constraints. Afterward, we explore an iterative control policy by utilizing the traditional mathematical programming method, which can ensure the liveness of the resultant controlled system. Comparing with the existing deadlock control policies reported in the literature, the proposed method can achieve a non-blocking controlled G-system with simple structure and high computational efficiency. Finally, a benchmark G-system example is used to substantiate the efficiency of the new method.

关键词： Petri net supervisory control G-systems resource partial orders mixed integer programming

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Improved Ant Colony System for VRPSPD with Maximum Distance Constraint

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Systems Engineering - Theory & Practice 2008年第1期28卷 132-140页

作者： Tao ZHANG Wen-xin TIAN Yue-jie ZHANG Shi-xin LIU School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai 200433 China Informatization Office in Center of Modern Education Technology of Shanghai Finance University Shanghai 201209 China Department of Computer Science and Engineering Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai 200433 China School of Information Science and Engineering Northeastern University Key Laboratory of Integrated Automation of Process Industry Ministry of Education Shenyang 110004 China

This article investigates the reverse logistics vehicle routing problem with a single depot, simultaneous distribution and collection of the goods by a homogeneous fleet of vehicles under the restrictions of maximum capacities and maximum distance. A mixed integer programming model is established. To solve the model, an Ant Colony System (ACS) approach combined with the pheromone updating strategy of ASRank and MMAS ant algorithm is proposed. In such approach, the vehicle residual loading capacity is introduced into the heuristic function considering the complex feature of fluctuating vehicle load. Moreover, the initial load is designed to be a random value correlated to the delivery and pick-up demands of the rest clients. The experimental study indicates that the proposed approach could improve the vehicle load rate and avoid the added total distance caused by the fluctuating load and the maximum capacity constraint. It could reach the satisfied solutions with high convergence speed in an acceptable computational time.

关键词： reverse logistic vehicle routing with simultaneous delivery and pick-up (VRPSPD) ant colony system (ACS) mixed integer programming

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Coordinated Production Planning and Scheduling Problem in a Foundry

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ARCHIVES OF FOUNDRY ENGINEERING 2017年第3期17卷 133-138页

作者： Stawowy, A. Duda, J. AGH Univ Sci & Technol Fac Management Ul Gramatyka 10 PL-30067 Krakow Poland

In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.

关键词： Heuristics Application of information technology to the foundry industry mixed integer programming Production planning Scheduling

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A Lagrangian Decomposition Algorithm for Robust Green Transportation Location Problem

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INTERNATIONAL JOURNAL OF ENGINEERING 2019年第1期32卷 85-91页

作者： Rouhani, A. Bashiri, M. Sahraeian, R. Shahed Univ Dept Ind Engn Tehran Iran

In this paper, a green transportation location problem is considered with uncertain demand parameter. Increasing robustness influences the number of trucks for sending goods and products, caused consequently, increase the air pollution. In this paper, two green approaches are introduced which demand is the main uncertain parameter in both. These approaches are addressed to provide a trade-off between using available trucks and buying new hybrid trucks for evaluating total costs beside air pollution. Due to growing complexity, a Lagrangian decomposition algorithm is applied to find a tight lower bound for each approach. In this propounded algorithm, the main model is decomposed into master and subproblems to speed up convergence with a tight gap. Finally, the suggested algorithm is compared with commercial solver regarding total cost and computational time. Due to computational results for the proposed approach, the Lagrangian decomposition algorithm is provided a close lower bound in less time against commercial solver.

关键词： Lagrangean Decomposition Robust Optimization Chance Constraint Green Transportation Location Problem mixed integer programming

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Machine Learning-Guided Dual Heuristics and New Lower Bounds for the Refueling and Maintenance Planning Problem of Nuclear Power Plants

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ALGORITHMS 2020年第8期13卷 185页

作者： Dupin, Nicolas Talbi, El-Ghazali Univ Paris Saclay Dept Comp Sci Lab Rech Informat LRI CNRS UMR 8623 F-91190 St Aubin France Univ Lille CNRS UMR 9189 Ctr Rech Informat Signal & Automat Dept Comp Sci F-59000 Lille France

This paper studies the hybridization of mixed integer programming (MIP) with dual heuristics and machine learning techniques, to provide dual bounds for a large scale optimization problem from an industrial application. The case study is the EURO/ROADEF Challenge 2010, to optimize the refueling and maintenance planning of nuclear power plants. Several MIP relaxations are presented to provide dual bounds computing smaller MIPs than the original problem. It is proven how to get dual bounds with scenario decomposition in the different 2-stage programming MILP formulations, with a selection of scenario guided by machine learning techniques. Several sets of dual bounds are computable, improving significantly the former best dual bounds of the literature and justifying the quality of the best primal solution known.

关键词： operations research mixed integer programming stochastic optimization dual bounds dual heuristics hybrid heuristics matheuristics machine learning EURO/ROADEF Challenge 2010 maintenance planning nuclear power plants power generation

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Mathematical modelling of waste rock management through incorporating open-pit waste rocks in underground stope filling: An environmental approach

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RESOURCES POLICY 2023年第PartB期85卷

作者： Esmailzadeh, Saghar Bakhtavar, Ezzeddin Mokhtarian-Asl, Mojtaba Sadiq, Rehan Hewage, Kasun Urmia Univ Technol Fac Environm Orumiyeh Iran Univ British Columbia Sch Engn Okanagan Campus Kelowna BC Canada Urmia Univ Technol Fac Environm Band Rd Orumiyeh *** Iran

Reducing the footprint of waste rock dumping would result in cost savings and mitigate the environmental impacts of mining. This study develops a mixed integer programming model for waste rock management, aimed at identifying the optimal dump location among surface waste dumps and underground stopes. The model generates an optimal waste rock dumping schedule and proposes the best destination, with the objectives of minimizing the total cost of waste rock hauling and maximizing the supply of filling materials for backfilling underground stopes from the waste rocks. By applying the model to a real metal mine, a total cost reduction of approximately 14% was accomplished by utilizing open-pit waste rocks as underground filling materials, replacing alternative sources. Sensitivity analysis approved that supplying the filling materials from waste rocks was a priority, which resulted in a reduction of 3,750,000 tonnes of dumping waste rocks on the surface and a significant reduction of the waste dump environmental footprint. The model not only improves the economics of mining operations but also mitigates the environmental impacts of open-pit waste rock dumping by using waste rocks for backfilling underground stopes instead of supplying materials from outside the mine.

关键词： Mine wastes management Environmental impact Filling materials Open-pit and underground mixed integer programming

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