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Facilities Location in the Supply Chain Network Using an iterated local search algorithm

FUZZY INFORMATION AND ENGINEERING 2023年第1期15卷 14-25页

作者： Seyedkolaei, Ali Abdi Nasseri, Seyed Hadi Univ Mazandaran Dept Appl Math Babolsar 48175 Iran Univ Mazandaran Res Ctr Optimizat & Logist Babolsar 48175 Iran

The supply chain design problem is one of the important problems in supply chain management. In this problem, the goal is to locate several facilities for distribution centers in different geographical areas to cover customer demands. In the model presented in this paper, customer demand is met through distribution centers, while these distribution centers supply products from manufacturing plants. In this paper, a mathematical model of integer linear programming is presented that, in addition to the optimal supply chain network design, considers the facility's location. This model aims to minimize the costs of sending products from the factory to distribution centers, from distribution centers to customers, and establishing distribution centers. To evaluate the proposed model, different network samples were created randomly on small, medium and large scales for experiments. In order to perform the experiments, a linear programming solver (LP Solver) and an iterated local search algorithm were used to compare the performance of each of these methods to find the optimal solution. These experiments show the superiority of the iterated local search algorithm compared to LP Solver in achieving the optimal solution in the shortest runtime for all instances.

关键词： supply chain distribution centers location iterated local search algorithm

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Resilient Many-to-Many Network Design of Fourth-Party Logistics based on iterated local search algorithm 35

Resilient Many-to-Many Network Design of Fourth-Party Logist...

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第35届中国控制会议

作者： LI Rui TONG Yujun SUN Fuming College of Electronic and Information Engineering Liaoning University of Technology

ISBN: (纸本)9781509009107

In order to offer a secure and efficient logistics service for many supply-demand pairs,the problem of resilient many-to-many network design for the fourth party logistics is studied,with the disruption of 3PL service nodes and 3PL transportation providers *** backup paths between supply-demand pairs are constructed to make the logistics network *** optimization model is formulated,which minimizes the total logistics costs with the resilience satisfying the required *** to the characteristic of the problem,an iterated local search algorithm is ***,several experiments are presented to test the significance of the model as well as the effectiveness of the proposed algorithm.

关键词： Fourth Party Logistics Network Design Many-to-Many Network Resilience iterated local search algorithm

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An iterated local search algorithm for flexible flow lines with sequence dependent setup times to minimize total weighted completion

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2012年第1期7卷 64-68页

作者： Khalili, Majid Islamic Azad Univ Dept Ind Engn Karaj Branch Karaj Iran

This paper explores flexible flow lines where setup times are sequence dependent. The optimization criterion is the minimization of total weighted completion time. We propose an An iterated local search algorithm (ILS) is proposed to tackle the problem. Among different meta-heuristics, the iterated greedy algorithm (IGA) has shown high performance for simpler problems such as flowshops. This paper looks at applying an adapted IGA to a much more complex problem where a well-known algorithm is adapted and evaluated. In this adaptation, a completely different decoding operator is applied, and hybridized with an effective local search and another temperature calculation procedure. Performance is also assessed using a comparison with a well-known random key genetic algorithm. A benchmark is set to evaluate the proposed algorithm, and the obtained ILS results are compared against some other algorithms. The effectiveness of ILS is demonstrated through this comparison.

关键词： scheduling flexible flow line sequence dependent setup time iterated local search algorithm

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Personalized travel itinerary recommendation enhancing by user interests and point-of-interest characteristics

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INFORMATION TECHNOLOGY & TOURISM 2025年 1-34页

作者： Chang, Chia-Wen Tsai, Chieh-Yuan Yao, Liguo Kuo, R. J. Tsai, Chi-Yang Yuan Ze Univ Dept Ind Engn & Management Taoyuan Taiwan Guizhou Normal Univ Sch Mech & Elect Engn Guiyang Peoples R China Guizhou Normal Univ Tech Engn Ctr Mfg Serv & Knowledge Engn Guiyang Peoples R China Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan

Personalized itinerary recommendations become critical as more people select travel as a primary leisure activity. Although online search engines and model-based recommendation systems can predict the points of interest (POIs) users are interested in, they are hard to generate an appropriate itinerary satisfying users' preferences and specific temporal or spatial constraints. In this study, a novel optimization method enhanced by user interests and POI characteristics is proposed. The proposed method incorporates an interest value prediction model considering the interaction feature deriving from the user's historical visiting sequence and visual feature from user-taken photo images. Aside from users' interest in POIs, the POI characteristic is included in itinerary planning to increase the chance of visiting popular and nearby sites. Then, travel itinerary planning is formulated as a variant orienteering problem that aims to find the optimal itinerary that maximizes user interest and POI characteristics under user-specified constraints. Finally, an iterated local search with Adaptive Perturbation (ILSAP) algorithm is proposed to escape the local optimum efficiently and explore other feasible solution regions. A real-life dataset from geo-tagged social media is implemented to demonstrate the benefits of the proposed personalized itinerary planning framework. The experiments show that the proposed method generates superior recommendations than popular baseline methods. In addition, the proposed ILSAP algorithm shows significant improvement compared to ILS algorithms with other perturbation strategies.

关键词： Personalized travel itinerary Interaction features Visual features POI characteristics iterated local search algorithm

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iterated local search method and mathematical model for sequence-dependent U-shaped disassembly line balancing problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 137卷 106056-000页

作者： Li, Zixiang Kucukkoc, Ibrahim Zhang, Zikai Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Technol Wuhan Hubei Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan Hubei Peoples R China Balikesir Univ Dept Ind Engn Cagis Campus TR-10195 Balikesir Turkey

Disassembly lines play an important role in disassembling end-of-life products and retrieving the valuable components. Sequence-dependent time increments are inevitable due to the interactions between two tasks in some occasions. This research provides the first attempt to study the sequence-dependent U-shaped disassembly line balancing problem (SUDLBP) with multiple objectives. A mixed-integer programming model is developed to solve the small-size instances optimally, where new expressions are developed to formulate the AND/OR precedence relations. Due to the NP-hard nature of this problem, a simple and effective iterated local search algorithm is developed for the first time. This algorithm utilizes modified NEH heuristic to achieve a high-quality initial solution. A new local search technic with referenced permutation and two neighbor structures is also embedded into it to obtain the local optimum solution. Computational tests demonstrate that the U-shaped lines outperform traditional straight lines in terms of the objective values. The comparative study on two sets of instances demonstrates that the proposed method outperforms the CPLEX solver in search speed and achieves a competing performance in comparison with other eight re-implemented algorithms.

关键词： Disassembly line balancing Sequence-dependent U-shaped disassembly line Integer programming iterated local search algorithm Metaheuristics

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The family capacitated vehicle routing problem

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EUROPEAN JOURNAL OF OPERATIONAL REsearch 2024年第3期314卷 836-853页

作者： Bernardino, Raquel Paias, Ana Univ Lisbon ISEG Sch Econ & Management Lisbon Portugal CEMAPRE REM Res Econ & Math Lisbon Portugal Univ Lisbon Fac Ciencias DEIO C6Piso 4 P-1749016 Lisbon Portugal Univ Lisbon Fac Ciencias CMAFcIO Lisbon Portugal

In this article, we address the family capacitated vehicle routing problem (F-CVRP), an NP-hard problem that generalizes both the FTSP and the capacitated vehicle routing problem. The F-CVRP has practical application in warehouse management in warehouses with scattered storage. We present several mixed integer linear programming formulations for this problem and establish a theoretical and empirical comparison. We also propose valid inequalities adapted from known routing problems from the literature. Some formulations are solved using a branch-and-cut algorithm, which is tested with a newly generated data set. The computational experiment allows us to identify the instances' most challenging characteristics and the exact methods' limitations. Finally, we develop an iterated local search (ILS) algorithm to efficiently obtain feasible solutions for the instances that could not be solved to proven optimality. The ILS algorithm is very efficient and can improve the upper bounds obtained by the exact methods within the set time limit.

关键词： Routing Family traveling salesman problem Projection results Branch-and-cut algorithm iterated local search algorithm

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The family traveling salesman problem with incompatibility constraints

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NETWORKS 2022年第1期79卷 47-82页

作者： Bernardino, Raquel Paias, Ana Univ Lisbon DEIO Fac Ciencias C6Piso 4 P-1749016 Lisbon Portugal Univ Lisbon Ctr Matemat Aplicacoes Fundamentais & Invest Oper Fac Ciencias Lisbon Portugal

In this article, we propose a new variant of the family traveling salesman problem (FTSP). The FTSP is an NP-hard problem that generalizes the traveling salesman problem. In the FTSP, the set of cities is partitioned into several families and one wants to find the minimum cost route that visits a given number of cities in each family. A new variant arises by introducing incompatibilities between families, that is, cities from incompatible families cannot be visited in the same route, and it is called the FTSP with incompatibility constraints (FTSP-IC). We propose compact and non-compact mixed integer linear programming models for the FTSP-IC where the incompatibility constraints are modeled by defining paths in a compatibility graph for each family. Additionally, we present a set of valid inequalities motivated by the incompatible families. The non-compact models and the valid inequalities were tested using a branch-and-cut framework. To evaluate the models we generated incompatibility matrices for benchmark instances of the FTSP, which are available in the website . With the branch-and-cut algorithm, we were able to obtain the optimal value of instances with up to 127 nodes. We also developed an ant colony optimization (ACO) algorithm and an iterated local search algorithm (ILS) to address the largest sized instances. Both metaheuristics are able to provide solutions for instances that the branch-and-cut algorithm cannot address and to improve the majority of the upper bounds obtained by the branch-and-cut algorithm in less computational time.

关键词： ant colony optimization algorithm branch‐ and‐ cut algorithm family traveling salesman problem incompatibility constraints iterated local search algorithm network flows valid inequalities

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local search-based metaheuristics for the robust distributed permutation flowshop problem

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APPLIED SOFT COMPUTING 2021年 105卷 107247-107247页

作者： Jing, Xue-Lei Pan, Quan-Ke Gao, Liang Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Expt & Network Informat Ctr Liaocheng 252000 Shandong Peoples R China Liaocheng Univ Sch Comp Sci & Technol Liaocheng 252000 Shandong Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

Distributed Permutation Flowshop Scheduling Problem (DPFSP) has become a hot issue in recent years. However, DPFSP with uncertain processing times (DPFSP_UPT) has not been addressed so far although real manufacturing systems often encounter various uncertain factors which make processing times uncertain. In this paper, two local-search based metaheuristics, i.e., an iterated Greedy algorithm (sIG) and an iterated local search algorithm (sILS), are presented to solve the DPFSP_UPT with makespan criterion. A robust model of expect-risk rule is used to describe the DPFSP_UPT. A valid heuristic based on the well-known NEH heuristic is proposed to initialize sIG and sILS. An acceleration algorithm is adapted to save computational efforts. A destruction procedure with dynamic sizes is presented to enhance the exploration capability for sIG. A feature with the characteristic that small changes in the solution can preserve the properties of good solutions in the iterative process is applied by sILS. Both sIG and sILS use multiple local search methods to produce promising solutions by exploiting diverse search areas. Extensive experiments show that the proposed sIG and sILS perform significantly better than the five competing algorithms adapted in the literature, but there is no significant difference between sIG and sILS and each has its own advantages for different instances. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Robust optimization Scenario iterated Greedy algorithm iterated local search algorithm NEH heuristic

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Heuristic optimisation for network restoration and expansion in compliance with the single-contingency policy

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第17期11卷 4264-4273页

作者： Thurner, Leon Scheidler, Alexander Probst, Alexander Braun, Martin Univ Kassel Dept Energy Management & Power Syst Operat D-34119 Kassel Germany Fraunhofer Inst Wind Energy & Energy Syst Technol D-34119 Kassel Germany Netze BW GmbH D-70567 Stuttgart Germany

Since failure of high- to medium-voltage (MV) transformers affect a large number of consumers, they are usually built with a redundancy to guarantee service restoration in the case of a single contingency. The redundancy can be provided by a backup transformer or by transferring the load to a neighbouring substation in case of failure. While a load transfer allows for more efficient use of transformers in normal operation, it also requires the MV network to be dimensioned with redundant transmission capability for the contingency case. In this study, the authors present their approach to determine if it is profitable in the long term to remove a backup transformer in intrinsically safe substations and handle resupply with load transfer to neighbouring substations instead. To this end, they compare the cost of the necessary network expansion to the costs of a backup transformer. They introduce an iterated local search algorithm for the calculation of emergency switching plans as well as expansion of the MV network. The methodology is applied to a large real MV network group, where reinforcing the network to allow a load transfer is cost efficient compared with the existing backup transformer in three of four substations.

关键词： transformer substations optimisation power transformers failure analysis redundancy power system restoration heuristic optimisation network restoration network expansion single-contingency policy high-to-medium-voltage transformers MV transformer failure service restoration substation redundant transmission capability iterated local search algorithm emergency switching plan calculation

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An Enhanced Intelligent Water Drops algorithm for Scheduling of an Agile Manufacturing System

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2016年第2期15卷 239-266页

作者： Teymourian, Ehsan Kayvanfar, Vahid Komaki, Gh M. Khodarahmi, Majtaba Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97331 USA Amirkabir Univ Technol Dept Ind Engn 424 Hafez Ave Tehran 158754413 Iran Case Western Reserve Univ Dept Elect Engn & Comp Sci 10900 Euclid Ave Cleveland OH 44106 USA Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran

This paper deals with an agile manufacturing system with two stages where the first stage is the machining stage including a single flexible machine while the second stage is assembly stage including parallel identical assembly machines. Products have an assembly structure where their parts should be processed at the first stage and then proceed to the assembly stage. The goal is to find the parts sequence which minimizes makespan. Since the studied problem is NP-hard, enhanced intelligent water drops (EIWD) algorithm as a new swarm-based nature inspired optimization algorithm is proposed. Also, artificial immune system (AIS) algorithm has been proposed to tackle the addressed problem. Computational results based on randomly generated instances show the effectiveness of the proposed technique.

关键词： Agile manufacturing system intelligent water drops algorithm iterated local search algorithm

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