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The strong network orientation problem

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2024年第1期31卷 192-220页

作者： Duhamel, Christophe Santos, Andrea Cynthia Normandie Univ LITIS INSA Rouen UNIHAVREUNIROUEN 25 Rue Philippe Lebon F-76600 Le Havre France

This study presents models and heuristics for solving the strong network orientation problem (SNOP), which can model several tactical optimization problems of setting directions in urban networks. The objective is to set an orientation for each edge in an undirected graph such that the resulting digraph is strongly connected and the total travel distance between any pair of nodes is minimized (or maximized). Investigating tactical optimization problems such as SNOP is motivated by several challenges in urban networks due to the growth of population in urban areas, large number of daily trips, increasing price of maintaining urban networks, and the need to reduce air pollution and passive noise. Thus, a new trend is to utilize the urban networks better. In this context, we first use a multicommodity flow formulation to model the minimization problem. The maximization version is modeled by using the dual formulation of the shortest path problem. Then, scalable heuristic strategies for solving SNOP are investigated. For such purpose, we first propose basic components such as constructive heuristics, perturbations and local searches. They are combined into several metaheuristics based on local searches, multi-start and evolutionary schemes, i.e. Multistart Local Search, Iterated Local Search (ILS), Relaxed ILS, Evolutionary Local Search (ELS), Relaxed ELS, and Variable Neighborhood Search. Computational experiments have been performed to analyze the proposed methods in terms of efficiency and quality of solutions, using grid instances and a graph from downtown Clermont-Ferrand in France.

关键词： urban network strong connectivity network design mixed integer linear programming heuristics

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Flexible job-shop scheduling problem with variable lot-sizing: An early release policy-based matheuristic

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 193卷

作者： Fan, Jiaxin Zhang, Chunjiang Tian, Shichen Shen, Weiming Gao, Liang Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan Peoples R China

Variable lot-sizing is a production pattern that allows operations of the same job type to conduct different lotsizing plans, which brings better flexibility compared to the routine consistent lot-sizing. However, under the variable lot-sizing scheme, since jobs in a sublot are likely to be released from multiple sublots of the previous operation, the sublot is forced to start being processed until all the predecessors are finished, and therefore the production efficiency suffers from a negative impact to a certain extent. To address the inconsistency, this paper investigates a flexible job-shop scheduling problem with variable lot-sizing (FJSP-VLS) for the makespan minimization. First, an early release (ER) policy is proposed to check where jobs of a sublot are transferred from and to accurately identify a set of predecessors, thus ensuring an earlier and feasible release moment for each sublot. Then, a monolithic mixed integer linear programming (MILP) model of the FJSP-VLS with the ER idea is established for the validation. Afterwards, a matheuristic is developed following the ER policy (MH ER ), where a simplified MILP model only for improving lot-sizing plans is embedded in a genetic algorithm (GA) as a powerful local search function. Finally, four groups of instances are extended from the Fdata benchmark to evaluate the performance of the proposed methods. Extensive experimental results suggest that the ER policy prominently raises the production efficiency by determining earlier release time for sublots. On the basis of this idea, the MILP-based local search brings significant improvements to incumbent solutions provided by the GA, and the MH ER is shown effective in a variety of FJSP-VLS scenarios.

关键词： Flexible job-shop scheduling Lot-streaming Variable lot-sizing Early release Matheuristic Genetic algorithm mixed integer linear programming

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Revisited Security Evaluation on Midori-64 against Differential Cryptanalysis

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2024年第2期18卷 478-493页

作者： Han, Guoyong Zhao, Hongluan Tianjin Normal Univ Management Sch Tianjin Peoples R China Tianjin Chengjian Univ Sch Sci Tianjin Peoples R China

In this paper, the mixed integer linear programming (MILP) model is improved for searching differential characteristics of block cipher Midori-64, and 4 search strategies of differential path are given. By using strategy IV, set 1 S-box on the top of the distinguisher to be active, and set 3 S-boxes at the bottom to be active and the difference to be the same, then we obtain a 5-round differential characteristics. Based on the distinguisher, we attack 12-round Midori-64 with data and time complexities of 2(63) and 2(103.83), respectively. To our best knowledge, these results are superior to current ones.

关键词： Midori-64 Block Cipher mixed integer linear programming Differential Distinguisher Differential Cryptanalysis

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A matheuristic with re-lot-sizing strategies for flexible job-shop rescheduling problem with lot-streaming and machine reconfigurations

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第3期319卷 747-762页

作者： Fan, Jiaxin Zhang, Chunjiang Yang, Fajun Shen, Weiming Gao, Liang Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan Peoples R China Shanghai Univ Sch Management Shanghai Peoples R China

This paper investigates a flexible job-shop rescheduling problem with lot-streaming and machine reconfigurations (FJRP-LSMR) for the total weighted tardiness minimization, where production setups between sublots are performed by assembling selected auxiliary modules to reconfigure machines. When a given long-term schedule is interrupted by dynamic events, such as machine breakdowns and job insertions, a rescheduling process is triggered to determine the lot-sizing plan, sublot sequences, and machine configurations simultaneously. A matheuristic with re-lot-sizing strategies (MHxzS) xzS ) is proposed to address the FJRP-LSMR, which takes the genetic algorithm as the main framework and introduces a mixed integer linear programming (MILP) based lot- sizing optimization (LSOxzS) xzS ) function to improve lot-sizing plans. Two re-lot-sizing strategies, namely complete re-lot-sizing and partial re-lot-sizing, are defined to reset more sublot sizes in rescheduling processes, thus the solution space that can be visited by the MILP model is greatly expanded for further improvements. Four groups of test instances and a complex real-world industrial case are adopted to evaluate the performance of the proposed methods. Extensive experimental results demonstrate that, with the help of re-lot-sizing strategies, the LSOxzS xzS can find high-quality lot-sizing plans within a short period of time, and the proposed MH xzS shows the best performance in the optimality, stability, and convergence.

关键词： Flexible job-shop rescheduling Lot-streaming Matheuristic Genetic algorithm mixed integer linear programming

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mixed integer linear programming formulations for probabilistic constraints

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OPERATIONS RESEARCH LETTERS 2012年第3期40卷 153-158页

作者： Vielma, J. P. Ahmed, S. Nemhauser, G. L. Univ Pittsburgh Dept Ind Engn Pittsburgh PA 15261 USA Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA

We introduce two new formulations for probabilistic constraints based on extended disjunctive formulations. Their strength results from considering multiple rows of the probabilistic constraints together. The properties of the first can be used to construct hierarchies of relaxations for probabilistic constraints, while the second provides computational advantages over other formulations. (C) 2012 Elsevier B.V. All rights reserved.

关键词： mixed integer linear programming Formulations Probabilistic constraints Chance constraints

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Model predictive control based optimal operation of smart city

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SUSTAINABLE CITIES AND SOCIETY 2024年 114卷

作者： Ishibashi, Takuma Furukakoi, Masahiro Uehara, Akie Masrur, Hasan Rashwan, Ahmed Krishna, Narayanan Mandal, Paras Takahashi, Hiroshi Senjyu, Tomonobu Univ Ryukyus Dept Elect & Elect Engn Okinawa 9030213 Japan Sanyo Onoda City Univ Dept Elect & Elect Engn Nagasaki 7560884 Japan King Fahd Univ Petr & Minerals Ind & Syst Engn Dept IRC Smart Mobil & Logist Dhahran 31261 Saudi Arabia Aswan Univ Fac Energy Engn Dept Elect Engn Sahary 81528 Egypt SASTRA Deemed Univ Dept Elect & Elect Engn Thanjavur 613401 India Univ Texas El Paso Dept Elect & Comp Engn El Paso TX 79968 USA Fuji Elect Co Ltd Tokyo 1410032 Japan

Rapid urbanization has resulted in a significant proportion of the world's population residing in urban areas. Cities are undergoing a transition towards the designation of smart cities, which aims to facilitate the efficient management of electrical and heating energy systems derived from renewable energy sources (RES). This paper presents a smart city model that incorporates RES, battery, grid and a combined cooling heat and power (CCHP) system. The smart city model deals with cooling, heating, and electric energy and applies a simple model predictive control (MPC) based approach for optimal operation. MPC method can be operated for future fluctuations by optimizing at the control horizon (N-C) while including the prediction horizon (N-P) in the optimization interval. The N-P and N-C parameters have a significant impact on the results, and their selection is an important consideration. This study uses MATLAB simulation to validate the effectiveness of MPC-based operations with a simplified forecasting model in a smart city utilizing RES and CCHP systems. The proposed method is easy to implement and shows sufficient performance while avoiding model complexity. In addition, the impact of N-C and N-P parameters on performance is investigated. The results show that the proposed method performs better when N-P is about 12 h.

关键词： Combined cooling heat and power mixed integer linear programming Model predictive control Optimization problem Renewable energy Smart city

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The berth allocation and quay crane assignment problem with crane travel and setup times

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COMPUTERS & OPERATIONS RESEARCH 2024年 162卷

作者： Correcher, Juan F. Perea, Federico Alvarez-Valdes, Ramon Univ Valencia Dept Estadist & Invest Operat Doctor Moliner 50 Burjassot 46100 Spain Univ Seville Dept Matemat Aplicada 2 Avda Reina Mercedes S-N Seville 41012 Spain Inst Matemat IMUS Avda Reina Mercedes S-N Seville 41012 Spain

In this paper, we propose a new approach for including quay crane travel and setup times in the berth allocation and quay crane assignment problem. We first develop a new mixed integer linear programming model (MILP) for the problem without setups (BACASP), in which berthing positions and times are considered as continuous variables. Several groups of valid inequalities are also set forth. Then, for the BACASP with crane travel and setup times, which we denote as BACASP-S, we propose two MILPs: the first is based on the previous BACASP formulation and the second on routing formulations. Due to the complexity of the BACASP-S, we also propose a genetic algorithm and an exact approach which combines various MILPs with the genetic algorithm. All methods and valid inequalities are computationally tested over two different sets of randomly generated instances. According to the results, the models and algorithms can optimally solve, in less than one hour, BACASP-S instances of up to 40 vessels within a quay one kilometer long and a time horizon of one week. Additionally, extensive experiments were conducted on a new large set of instances to assess the effect of various BACASP-S input parameters on the computation effort required to solve the problem. Ceteris paribus, the computational effort required seems to increase with decreasing number of cranes, while vessel processing times and crane setup times seem not to affect it.

关键词： Berth allocation Quay crane assignment Setup time mixed integer linear programming Combinatorial optimization Port logistics Container terminal

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A genetic algorithm with critical path-based variable neighborhood search for distributed assembly job shop scheduling problem

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SWARM AND EVOLUTIONARY COMPUTATION 2024年 85卷

作者： Tian, Shichen Zhang, Chunjiang Fan, Jiaxin Li, Xinyu Gao, Liang Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China

Production scheduling in distributed manufacturing systems has become an active research field, where largesized complicated products, such as airplanes and ships, are taken as the primary focus. This paper investigates a distributed assembly job shop scheduling problem (DAJSP) which consists of two production phases. The first stage processes components in several job shops, and the second stage assembles the processed parts into final products. First, a mixed integer linear programming (MILP) model is established to describe the problem with minimizing maximum completion time and find optimal schedules for small-scale scenarios. Afterwards, a genetic algorithm with variable neighborhood search (GA-VNS) is proposed to address more complex instances, which adopts the genetic algorithm as the main framework and employs the variable neighborhood search for exploration. A problem -specific three -vector encoding scheme is designed to represent three decision -making processes of the DAJSP accordingly. To improve candidate solutions, a disjunctive graph model for DAJSP is formulated and three critical path -based neighborhood structures which directly perform on encoding vectors are designed. Numerical experiments are conducted on four groups of instances with different scales and the experimental results demonstrate the effectiveness of the proposed MILP model and GA-VNS. To sum up, the proposed GA-VNS shows the best performance on 30 instances out of 40 instances, while the superior stability has also been proved by statistical tests. In addition, two complicated DAJSP cases are abstracted from an enterprise for fabricating large complex components to further validate the GA-VNS.

关键词： Distributed assembly job shop scheduling Genetic algorithm Variable neighborhood search mixed integer linear programming Critical path

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Maximum capture problem based on paired combinatorial weibit model to determine park-and-ride facility locations

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2024年 179卷

作者： Kitthamkesorn, Songyot Chen, Anthony Ryu, Seungkyu Opasanon, Sathaporn Chiang Mai Univ Excellence Ctr Infrastruct Technol & Transportat E Dept Civil Engn Sch Engn Chiang Mai 50200 Thailand Hong Kong Polytech Univ Dept Civil & Environm Engn Hong Kong Peoples R China Hong Kong Polytech Univ Shenzhen Res Inst Shenzhen Peoples R China Daejeon Sejong Res Inst Sejong City Policy Res Div Daejeon South Korea Thammasat Univ Fac Commerce & Accountancy Dept Int Business Logist & Transport Bangkok 10200 Thailand

Park-and-ride (P&R) facilities are key components in encouraging people to use the transit system by allowing them to leave their private vehicles at certain locations. The well-known multinomial logit (MNL) model is often used to develop a random utility maximization-based mathematical programming formulation to determine P&R facility locations. According to the independently and identically distributed (IID) assumption, the MNL model cannot account for the route similarity and user heterogeneity. This study provides a new mixed integer linear programming (MILP) formulation by incorporating a newly developed paired combinatorial weibit (PCW) model to relax the IID assumption for determining the optimal P&R facility location. Specifically, the incorporation of a copula derived from a generalized extreme value (GEV) model addresses the issue of route overlap within the context of the PCW model. In addition, using the Weibull distribution permits the consideration of heterogeneous perception variance. Its two-level tree structure for evaluating the marginal and conditional probabilities allows a linearization scheme to obtain a set of linear constraints. Numerical examples reveal the influence of the IID assumption relaxation on the results. The two probabilities from the tree structure and the binary location variables are combined to present a corresponding PCW model under open/close P&R facility solution. According to the degree of route overlapping and route-specific perception variance, the fare structure, particularly the distance-based scheme, has an impact on the number of P&R users and location at optimum.

关键词： mixed integer linear programming Park and ride Paired combinatorial weibit Generalized extreme value Weibull distribution

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Optimal establishment of processing unit and partner selection problem of perishable product supply chain: apple case study of India

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RAIRO-OPERATIONS RESEARCH 2024年第5期58卷 4477-4497页

作者： Bhardwaj, Manisha Agrawal, Rajat Amity Univ Amity Business Sch Noida Uttar Pradesh India Indian Inst Technol Roorkee Dept Management Studies Roorkee India

Decentralized supply chain operation in India adds to inefficiency in management and control difficulties for perishable product supply chain (PPSC). One of the important categories of factors that underly the problem in supply chain is the establishment of processing units that results in end - product distribution. This paper presents an optimal establishment of processing unit around production area for apple supply chain as a case study of India. This study proposed amalgamation of mixed integer linear programming (MILP) and colored petri nets (CPN) to model the PPSC. The mathematical model was set up in regard with capacity of processing unit and transportation cost with continuation in partner selection using MILP approach. The simulation model directs the maximization of system performance by running in CPN environment. The values of the results are subjected to transportation cost and production area with estimate of 25% loss during post harvesting such as transportation and environmental variation. The results corresponding to the case study provided an optimal establishment of processing units. Further, the specific partner associated with the facility and transportation cost. Decision-makers can identify the set of partners from the set of facilities dependent upon the transportation cost for further supply of product using a threshold values. Thereby, the model can be used as a decision-making system for processing companies to result in efficient PPSC management. The developed model was tested and validated on case study to demonstrate our approach's applicability.

关键词： Perishable product supply chain fresh produce colored petri nets mixed integer linear programming

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