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An Effective Biogeography-Based Optimization algorithm for Flow Shop Scheduling with Intermediate Buffers

Chinese Journal of Electronics 2018年第6期27卷 1141-1150页

作者： LIU Shufen WANG Pengfei YAO Zhilin College of Computer Science and Technology Jilin University

This paper proposes an Effective biogeography-based optimization(EBBO) algorithm for solving the flow shop scheduling problem with intermediate buffers to minimize the Total flow time(TFT). Discrete job permutations are used to represent individuals in the EBBO so the discrete problem can be solved directly. The NEH heuristic and NEH-WPT heuristic are used for population initialization to guarantee the diversity of the solution. Migration and mutation rates are improved to accelerate the search process. An improved migration operation using a two-points method and mutation operation using inverse rules are developed to prevent illegal solutions. A new local search algorithm is proposed for embedding into the EBBO algorithm to enhance local search *** simulations and comparisons demonstrated the superiority of the proposed EBBO algorithm in solving the flow shop scheduling problem with intermediate buffers with the TFT criterion.

关键词： Flow shop scheduling Intermediate buffer Total flow time(TFT) Biogeography-based optimization algorithm local search algorithm

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Optimisation approaches for supply chain planning and scheduling under demand uncertainty

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CHEMICAL ENGINEERING REsearch & DESIGN 2018年 138卷 341-357页

作者： Aguirre, Adrian M. Liu, Songsong Papageorgiou, Lazaros G. UCL Dept Chem Engn Ctr Proc Syst Engn Torrington Pl London WC1E 7JE England Swansea Univ Sch Management Bay CampusFabian Way Swansea SA1 8EN W Glam Wales

This work presents efficient MILP-based approaches for the planning and scheduling of multiproduct multistage continuous plants with sequence-dependent changeovers in a supply chain network under demand uncertainty and price elasticity of demand. This problem considers multiproduct plants, where several products must be produced and delivered to supply the distribution centres (DCs), while DCs are in charge of storing and delivering these products to the final markets to be sold. A hybrid discrete/continuous model is proposed for this problem by using the ideas of the Travelling Salesman Problem (TSP) and global precedence representation. In order to deal with the uncertainty, we proposed a Hierarchical Model Predictive Control (HMPC) approach for this particular problem. Despite of its efficiency, the final solution reported still could be far from the global optimum. Due to this, local search (LS) algorithms are developed to improve the solution of HMPC by rescheduling successive products in the current schedule. The effectiveness of the proposed solution techniques is demonstrated by solving a large-scale instance and comparing the solution with the original MPC and a classic Cutting Plane approach adapted for this work. (C) 2018 The Authors. Published by Elsevier B.V. on behalf of Institution of Chemical Engineers.

关键词： Supply chain network Planning and scheduling under uncertainty MILP Model predictive control local search algorithm

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A Partial Decision Scheme for local search algorithms for Distributed Constraint Optimization Problems 17

A Partial Decision Scheme for Local Search Algorithms for Di...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Zhepeng Yu Ziyu Chen Jingyuan He Yancheng Deng College of Computer Science Chongqing University

ISBN: (纸本)9781510855076

local search algorithms are widely adopted in solving large-scale Distributed Constraint Optimization Problems (DCOPs) However, since each agent always makes its value decision based on the values of its neighbors in local search, those algorithms usually suffer from local premature convergence More concretely, an agent cannot make a wise decision with poor values of its neighbors since its decision space is bound up with those poor values In this paper, we propose a Partial Decision Scheme (PDS) to relax the decision space of an agent by ignoring the value of its neighbor which has the bad impact on its local benefits. The PDS comprises two partial decision processes trigger partial decision and recursive partial decision The former is iteratively performed by agents who cannot enhance their local benefits unilaterally to break out of potential local optima. The latter is recursively performed by neglected agents to improve global benefits Besides, the trigger conditions along with a self-adaptive probability are introduced to control the use of PDS The PDS can be easily applied to any local search algorithm to overcome its local premature convergence with a small additional overhead In our theoretical analysis, we prove the feasibility and convergence of PDS Moreover, the experimental results also demonstrate the superiority of the use of PDS in the typical local search algorithms over state-of-the-art local search algorithms.

关键词： Multi-agent System Distributed Constraint Optimization Problem Incomplete algorithm local search algorithm Partial Decision searchING algorithm Multi-agent systems pendrin Planetary Data System Constrained optimization Agents Neighbor bouse Partial

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Multi-objective mapping of full-mission simulators on heterogeneous distributed multi-processor systems

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JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS 2018年第4期15卷 449-460页

作者： Ayari, Rabeh Hafnaoui, Imane Aguiar, Alexandra Gilbert, Patricia Galibois, Michel Rousseau, Jean-Pierre Beltrame, Giovanni Nicolescu, Gabriela Ecole Polytech Montreal 2900 Blvd Eduard Monpetit Montreal PQ H3T 1J4 Canada CAE Global Dev Engn Dept Montreal PQ Canada CAE Montreal PQ Canada

Full-mission simulators (FMSs) are considered the most critical simulation tool belonging to the flight simulator family. FMSs include a faithful reproduction of fighter aircraft. They are used by armed forces for design, training, and investigation purposes. Due to the criticality of their timing constraints and the high computation cost of the whole simulation, FMSs need to run in a high-performance computing system. Heterogeneous distributed systems are among the leading computing platforms and can guarantee a significant increase in performance by providing a large number of parallel powerful execution resources. One of the most persistent challenges raised by these platforms is the difficulty of finding an optimal mapping of n tasks on m processing elements. The mapping problem is considered a variant of the quadratic assignment problem, in which an exhaustive search cannot be performed. The mapping problem is an NP-hard problem and solving it requires the use of meta-heuristics, and it becomes more challenging when one has to optimize more than one objective with respect to the timing constraints. Multi-objective evolutionary algorithms have proven their efficiency when tackling this problem. Most of the existent works deal with the task mapping by considering either a single objective or homogeneous architectures. Therefore, the main contribution of this paper is a framework based on the model-driven design paradigm allowing us to map a set of intercommunicating real-time tasks making up the FMS model onto the heterogeneous distributed multi-processor system model. We propose a multi-objective approach based on the well-known optimization algorithm Non-dominated Sorting Genetic algorithm-II satisfying the tight timing constraints of the simulation and minimizing makespan, communication cost, and memory consumption simultaneously.

关键词： Full-mission simulators real-time systems heterogeneous computing architectures mapping problem schedulability analysis multi-objective optimization local search algorithm meta-heuristics

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Research on Control Strategy of Large-scale Electric Heat Pumps Considering Power Supply Safety

Research on Control Strategy of Large-scale Electric Heat Pu...

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International Conference on Power System Technology (POWERCON)

作者： Guo, Wenxin Yu, Kun Chen, Xingying Huang, Xiaoshu Gan, Lei Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Jiangsu Peoples R China

ISBN: (纸本)9781538664612

After the implementation of the "Electric power alternatives" scheme, large-scale electric heat pumps (EHPs) were used to replace the previous coal-fired boilers, which makes the distribution network appears heavy load, overload and even affected the normal power consumption of users. Based on the state-queueing control model, the following operation control of the EHP is carried out for the purpose of ensuring its safe operation: using an improved K-means clustering algorithm suitable for the control group of the EHPs, the EHPs with similar control characteristics are divided into a same control group and carrie out state-queueing control;A local search algorithm is used to optimize the load operation for the combined optimization of the sub-range operation mode of each EHP in each distribution area. An example is given to verify that the proposed operation control strategy can avoid overloading of the distribution network and ensure normal power supply and safe operation of the system when large-scale EHP loads are concentrated.

关键词： Electric power alternatives electric heat pump power supply security control strategy local search algorithm

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Rules-based heuristic approach for the U-shaped assembly line balancing problem

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APPLIED MATHEMATICAL MODELLING 2017年 48卷 423-439页

作者： Li, Ming Tang, Qiuhua Zheng, Qiaoxian Xia, Xuhui Floudas, C. A. Wuhan Univ Sci & Technol Coll Sci Wuhan 430065 Hubei Peoples R China Wuhan Univ Sci & Technol Coll Mech & Automat Wuhan 430081 Hubei Peoples R China Hubei Univ Sch Comp Sci & Informat Engn Wuhan 430062 Hubei Peoples R China Princeton Univ Dept Chem & Biol Engn Princeton NJ 08544 USA

The type-2 U-shaped assembly line balancing problem is important for many just-in-time manufactures, but an efficient algorithm is not available at present. Thus, in this study, a novel heuristic approach based on multiple rules and an integer programming model is proposed to address this problem. In the proposed approach, three rules are systematically grouped together, i.e., task selection, task assignment, and task exchange rules. The sufficient conditions for implementing the exchange rules are proposed and proved. Thirteen small or medium scale benchmark issues comprising 63 instances were solved, where the computational results demonstrate the efficiency and effectiveness of the proposed method compared with integer programming. The computational results obtained for 18 examples comprising 121 instances demonstrate that the task exchange rules significantly improve the computational accuracy compared with the traditional heuristic. Finally, 30 new standard instances produced by a systematic data generation process were also solved effectively by the proposed approach. The proposed heuristic approach with multiple rules can provide a theoretical basis for other local search algorithms, especially for addressing issues such as the U-Shaped assembly line balancing problem. (C) 2017 Published by Elsevier Inc.

关键词： Heuristic approach local search algorithm Task exchange rule U-shaped assembly line balancing problem

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Correction Method of Reference Flux for Maximum Torque per Ampere Control in Direct-Torque-Controlled IPMSM Drives

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IEEJ JOURNAL OF INDUSTRY APPLICATIONS 2017年第1期6卷 12-18页

作者： Shinohara, Atsushi Inoue, Yukinori Morimoto, Shigeo Sanada, Masayuki Osaka Prefecture Univ Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

In this paper, a maximum torque per ampere (MTPA) control strategy for direct-torque-controlled interior permanent magnet synchronous motor (IPMSM) drives is proposed. For current-controlled IPMSM drives, many methods have been proposed, in which the periodic signals are injected into reference current vectors. On the other hand, the direct-torque-controlled IPMSM drives require the torque and stator flux linkage magnitude as their references. The proposed method injects signals into the reference flux in a manner similar to that used for the signal injections in current-controlled IPMSM drives. The main feature of the proposed method is the ability to search the optimal current directly and successively using a local search algorithm. Therefore, variations in the parameters can be considered. The simulation and experimental results validate the proposed method.

关键词： permanent magnet synchronous motors direct torque control maximum torque per ampere control local search algorithm

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Design of Food Exchange List for Obesity using Modified local search 13

Design of Food Exchange List for Obesity using Modified Loca...

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13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Dholvitayakhun, Achara Kluabwang, Jukkrit Rajamangala Univ Technol Lanna Tak Fac Sci & Agr Technol Muang 63000 Tak Thailand Rajamangala Univ Technol Lanna Tak Fac Engn Dept Elect Engn Muang 63000 Tak Thailand

ISBN: (纸本)9781467397490

This article presents an application of modified local search (MLS) to design meal's plan for obestity by food exchange list. Both computational experiment and implementation are elaborated. Three obesity cases have been tested with 10 independent trials. The minimum searching time of case I, II, and III are 0.1784, 0.0384 and 0.0784 seconds, respectively. An implementation has selected an obtained result from case II with total energy 1,925 kcal per day, carbohydrate 289 g, protein 93 g and lipid 42 g. After preparation, three main courses, breakfast, lunch and dinner, are macaroni with shrimp soup, baked rice with pine apple and a set of rice with fried mixed vegetables and sour soup, respectively.

关键词： local search algorithm food exchange list ideal body weight

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Inscribed ball and enclosing box methods for the convex maximization problem

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OPTIMIZATION LETTERS 2016年第2期10卷 417-432页

作者： Guerard, Guillaume Tseveendorj, Ider Univ Versailles Lab PRiSM 45 Ave Etats Unis F-78035 Versailles France

Many important classes of decision models give rise to the problem of finding a global maximum of a convex function over a convex set. This problem is known also as concave minimization, concave programming or convex maximization. Such problems can have many local maxima, therefore finding the global maximum is a computationally difficult problem, since standard nonlinear programming procedures fail. In this article, we provide a very simple and practical approach to find the global solution of quadratic convex maximization problems over a polytope. A convex function achieves its global maximum at extreme points of the feasible domain. Since an inscribed ball does not contain any extreme points of the domain, we use the largest inscribed ball for an inner approximation while a minimal enclosing box is exploited for an outer approximation of the domain. The approach is based on the use of these approximations along with the standard local search algorithm and cutting plane techniques.

关键词： local search algorithm Non-convex optimization Convex maximization Inscribed ball

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Integrated multi-track station layout design and train scheduling models on railway corridors

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TRANSPORTATION REsearch PART C-EMERGING TECHNOLOGIES 2016年 69卷 91-119页

作者： Qi, Jianguo Yang, Lixing Gao, Yuan Li, Shukai Gao, Ziyou Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

The dwelling capacity of the station (mainly determined by its multi-track layout) is a practically significant factor to influence the quality of the train schedules, especially in a busy railway corridor with heterogeneous trains and complex operations. To improve the passing capacity and transportation efficiency, this paper focuses on a network design problem over a railway corridor, in which some critical stations are considered to enlarge the number of siding tracks or platforms within the budget constraints. To evaluate the quality of design strategies, the construction cost and total travel time in the corresponding optimal train schedule are adopted as evaluation indexes. Based on two specific modeling methodologies, two types of optimization models are particularly formulated with different considerations. One is a single-level linear mixed-integer programming (S-LMIP) model based on the space-time network representation method;the other is a bi-level programming model associated with the platform choice-based method, where the upper level of the proposed model aims to design new siding tracks/platforms in the candidate stations, and the lower level is a train scheduling model with assigning the tracks for each train at each station. The commercial software GAMS with CPLEX solver and local searching based heuristic with integrated CPLEX solver are respectively employed to solve the near-optimal solutions for these two types of models. Finally, two sets of examples, in which a sample railway corridor and the Wuhan-Guangzhou high-speed railway corridor are adopted as the experimental environments, are implemented to illustrate the performance and effectiveness of the proposed approaches. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Train scheduling Multi-track station layout design Linear mixed-integer programming model Bi-level optimization model local search algorithm

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