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14th International Conference on Intelligent Computing (ICIC)

作者： Oztop, Hande Tasgetiren, M. Fatih Eliiyi, Deniz Tursel Pan, Quan-Ke Yasar Univ Dept Ind Engn Bornova Turkey Yasar Univ Dept Int Logist Management Bornova Turkey Huazhong Univ Sci & Technol State Key Lab Wuhan Hubei Peoples R China

ISBN: (纸本)9783319959573;9783319959566

Permutation flow shop scheduling problem (PFSP) is a well-known problem in the scheduling literature. Even though many multi-objective PFSPs are presented in the literature with the objectives related to production efficiency and customer satisfaction, studies considering energy consumption and environmental effects in scheduling is very seldom. In this paper, the trade-off between total energy consumption (TEC) and total flow time is investigated in a PFSP environment, where the machines are assumed to operate at varying speed levels. A multi-objective mixed integer linear programming model is proposed based on a speed-scaling strategy. Due to the NP-complete nature of the problem, an efficient multi-objective iterated greedy (IGALL) algorithm is also developed. The performance of IGALL is compared with model performance in terms of quality and cardinality of the solutions.

关键词： Permutation Flowshop Scheduling Energy efficient scheduling Multi-objective optimization iterated greedy algorithm Heuristic optimization

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Automatic algorithm Configuration for the Permutation Flow Shop Scheduling Problem Minimizing Total Completion Time 1

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18th European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP)

作者： Brum, Artur Ritt, Marcus Univ Fed Rio Grande Sul UFRGS Inst Informat Porto Alegre RS Brazil

ISBN: (数字)9783319774497

ISBN: (纸本)9783319774497;9783319774480

Automatic algorithm configuration aims to automate the often time-consuming task of designing and evaluating search methods. We address the permutation flow shop scheduling problem minimizing total completion time with a context-free grammar that defines how algorithmic components can be combined to form a full heuristic search method. We implement components from various works from the literature, including several local search procedures. The search space defined by the grammar is explored with a racing-based strategy and the algorithms obtained are compared to the state of the art.

关键词： Automatic algorithm configuration iterated greedy algorithm iterated local search Flow shop scheduling problem Total completion time

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Efficient heuristic for solving non-permutation flow-shop scheduling problems with maximal and minimal time lags

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 113卷 160-184页

作者： Ye, Song Zhao, Ning Li, Kaidian Lei, Chuanjin Univ Sci & Technol Beijing Sch Mech Engn Xueyuan Rd 30 Beijing 100083 Peoples R China

Flow-shop scheduling problem is an attractive subject in the scheduling field, which has attracted the attention of many researchers in the past five decades. However, few studies focused on non permutation flow-shop problems with time lag consideration. In the present work, the non permutation flow-shop scheduling problem with time lags has been studied to minimize the makespan as a performance measure. First, we obtain a near-optimal permutation solution using the permutation flow-shop problem (PFSP) heuristic. Then, an effective iterated greedy heuristic, which can identify high quality non-permutation solutions, is presented. Using the neighbourhood non-PFSP searching heuristic, we searched for non-PFSP schedules using the proposed heuristic algorithms in the second stage. Finally, the computational results were used to evaluate the performance and effectiveness of the proposed heuristic. The proposed heuristics were able to find near optimal non-PFSP solutions with very short computational time. Thus, the proposed algorithms is efficient and can be used in industrial applications. Moreover, the proposed heuristic algorithms are very simple to implement, which is attractive for industrial applications. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Non-permutation Flow shop Time lags Makespan iterated greedy algorithm

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Minimizing the total completion time in a two-machine flowshop problem with time delays

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ENGINEERING OPTIMIZATION 2016年第7期48卷 1164-1181页

作者： Msakni, Mohamed Kais Khallouli, Wael Al-Salem, Mohamed Ladhari, Talel Qatar Univ Mech & Ind Engn Doha Qatar Umm Al Qura Univ Coll Business Umm Al Qura Saudi Arabia Univ Tunis Ecole Super Sci Econom & Commerciales Tunis Tunis Tunisia

This article proposes to solve the problem of minimizing the total completion time in a two-machine permutation flowshop environment in which time delays between the machines are considered. For this purpose, an enumeration algorithm based on the branch-and-bound framework is developed, which includes new lower and upper bounds as well as dominance rules. The computational study shows that problems with up to 40 jobs can be solved in a reasonable amount of time.

关键词： flowshop time lags lower bounds branch-and-bound iterated greedy algorithm

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A hybrid algorithmic model for the minimum weight dominating set problem

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SIMULATION MODELLING PRACTICE AND THEORY 2016年 64卷 57-68页

作者： Bouamama, Salim Blum, Christian Univ Msila Dept Comp Sci Msila 28000 Algeria Univ Basque Country UPV EHU Dept Comp Sci & Artificial Intelligence San Sebastian Spain Basque Fdn Sci Ikerbasque Bilbao Spain

iterated greedy algorithms belong to the class of stochastic local search methods. They are based on the simple and effective principle of generating a sequence of solutions by iterating over a constructive greedy heuristic using destruction and construction phases. This paper, first, presents an efficient randomized iterated greedy approach for the minimum weight dominating set problem, where-given a vertex-weighted graph-the goal is to identify a subset of the graphs' vertices with minimum total weight such that each vertex of the graph is either in the subset or has a neighbor in the subset. Our proposed approach works on a population of solutions rather than on a single one. Moreover, it is based on a fast randomized construction procedure making use of two different greedy heuristics. Secondly, we present a hybrid algorithmic model in which the proposed iterated greedy algorithm is combined with the mathematical programming solver CPLEX. In particular, we improve the best solution provided by the iterated greedy algorithm with the solution polishing feature of CPLEX. The simulation results obtained on a widely used set of benchmark instances shows that our proposed algorithms outperform current state-of-the-art approaches. (C) 2015 Elsevier B.V. All rights reserved.

关键词： iterated greedy algorithm Minimum weight dominating set problem Hybrid model

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Accelerated methods for total tardiness minimisation in no-wait flowshops

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2015年第4期53卷 1002-1018页

作者： Ding, Jianya Song, Shiji Zhang, Rui Gupta, Jatinder N. D. Wu, Cheng Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Nanchang Univ Sch Econ & Management Nanchang Peoples R China Univ Alabama Coll Business Adm Huntsville AL 35899 USA

For the minimisation of total tardiness in no-wait flowshops, objective incremental properties are investigated in this paper to speed up the evaluation of candidate solutions. To explore the properties, we introduce a new concept of sensitive jobs and identify through experiments that the proportion of such jobs is very small. Instead of evaluating the tardiness of each job, we focus on the evaluation of sensitive jobs which will help to reduce the computational efforts. With these properties, the time complexity of the NEH-insertion procedure is reduced from [GRAPHICS] to approximately [GRAPHICS] in average. Then, an accelerated NEH algorithm and an accelerated iterated greedy algorithm are designed for the problem. Since the NEH-insertion procedure constitutes the main computational burden for both algorithms, these algorithms will benefit directly from the speedup. Numerical computations show that the accelerated algorithms perform 10-40 times faster than the original algorithms on the middle- and large-sized instances. In addition, comparisons show that the proposed algorithms perform more efficiently and effectively than the existing heuristics and meta-heuristics.

关键词： no-wait flowshop NEH-insertion total tardiness iterated greedy algorithm objective incremental properties

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Minimizing makespan for flow shop scheduling problem with intermediate buffers by using hybrid approach of artificial immune system

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APPLIED SOFT COMPUTING 2015年 28卷 44-56页

作者： Abdollahpour, Sana Rezaeian, Javad Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran

In this study, three new meta-heuristic algorithms artificial immune system (AIS), iterated greedy algorithm (IG) and a hybrid approach of artificial immune system (AIS-IG) are proposed to minimize maximum completion time (makespan) for the permutation flow shop scheduling problem with the limited buffers between consecutive machines. As known, this category of scheduling problem has wide application in the manufacturing and has attracted much attention in academic fields. Different from basic artificial immune systems, the proposed AIS-IG algorithm is combined with destruction and construction phases of iterated greedy algorithm to improve the local search ability. The performances of these three approaches were evaluated over Taillard, Carlier and Reeves benchmark problems. It is shown that the AIS-IG and AIS algorithms not only generate better solutions than all of the well-known meta heuristic approaches but also can maintain their quality for large scale problems. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Flow shop scheduling problem Limited buffers Artificial immune system iterated greedy algorithm

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A Populated Local Search with Differential Evolution for Blocking Flowshop Scheduling Problem

A Populated Local Search with Differential Evolution for Blo...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Tasgetiren, M. Fatih Pan, Quan-Ke Kizilay, Damla Suer, Gursel Yasar Univ Dept Ind Engn Izmir Turkey Huazhong Univ Sci & Technol State Key Lab Wuhan Peoples R China Ohio Univ Ind & Syst Engn Dept Athens OH 45701 USA

ISBN: (纸本)9781479974924

This paper presents a populated local search algorithm through a differential evolution algorithm for solving the blocking flowshop scheduling problem under makespan criterion. iterated greedy and iterated local search algorithms are simple but extremely effective in solving scheduling problems. However, these two algorithms have some parameters to be tuned for which it requires a design of experiments with expensive runs. In this paper, we propose a novel multi-chromosome solution representation for both local search and differential evolution algorithm which is responsible for providing the parameters of IG and ILS algorithms. In other words, these parameters are learned by the differential evolution algorithm in order to guide the local search process. We also present the greedy randomized adaptive search procedure (GRASP) for the problem on hand. The performance of the populated local search algorithm with differential evolution algorithm and the GRASP heuristic is tested on Taillard's benchmark suite and compared to the best performing algorithms from the literature. Ultimately, 90 out of 120 problem instances are further improved.

关键词： blocking flowshop iterated local search iterated greedy algorithm constructive heuristics

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Cyclic scheduling of perishable products in parallel machine with release dates, due dates and deadlines

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年第Oct.期156卷 1-12页

作者： Shirvani, Nargess Ruiz, Ruben Shadrokh, Shahram Sharif Univ Technol Dept Ind Engn Tehran Iran Univ Politecn Valencia Inst Tecnol Informat Ciudad Politecn Innovac Grp Sistemas Optimizac Aplicada Valencia 46022 Spain

This paper deals with a realistic cyclic scheduling problem in the food industry environment in which parallel machines are considered to process perishable jobs with given release dates, due dates and deadlines. Jobs are subject to post-production shelf life limitation and must be delivered to retailers during the corresponding time window bounded by due dates and deadlines. Both early and tardy jobs are penalized by partial weighted earliness/tardiness functions and the overall problem is to provide a cyclic schedule of minimum cost. A mixed integer programming model is proposed and a heuristic solution beside an iterated greedy algorithm is developed to generate good and feasible solutions for the problem. The proposed MIP, heuristic and iterated greedy produce a series of solutions covering a wide range of cases from slow optimal solutions to quick and approximated schedules. (C) 2014 Published by Elsevier B.V.

关键词： Parallel machine scheduling Perishable products Partial weighted earliness/tardiness Due date Deadline Release date iterated greedy algorithm

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A Discrete Artificial Bee Colony algorithm for the Team Orienteering Problem with Time Windows

A Discrete Artificial Bee Colony Algorithm for the Team Orie...

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IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS)

作者： Karabulut, Korhan Tasgetiren, M. Fatih Yasar Univ Software Engn Dept Selcuk Yasar Campus Izmir Turkey Yasar Univ Dept Ind Engn Izmir Turkey

ISBN: (纸本)9781467359054

This paper presents a discrete artificial bee colony algorithm (DABC) for solving the team orienteering problem with time windows (TOPTW). The proposed algorithm employs a destruction and construction procedure to generate neighboring food sources in the framework of the DABC algorithm. In addition, a variable neighborhood descent (VND) algorithm is developed to enhance the solution quality. The performance of the algorithm was tested on a benchmark set from the literature. Experimental results show that the proposed DABC algorithm is competitive to the best performing algorithms from the literature. Ultimately, 11 instances are further improved by the proposed DABC algorithm.

关键词： orienteering problem with time windows artificial bee colony algorithm iterated greedy algorithm swarm intelligence heuristic optimization

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