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bi-objective scheduling on uniform parallel machines considering electricity cost

ENGINEERING OPTIMIZATION 2018年第1期50卷 19-36页

作者： Zeng, YiZeng Che, Ada Wu, Xueqi Northwestern Polytech Univ Sch Management Xian Shaanxi Peoples R China

This article investigates a bi-objective scheduling problem on uniform parallel machines considering electricity cost under time-dependent or time-of-use electricity tariffs, where electricity price changes with the hours within a day. The aim is to minimize simultaneously the total electricity cost and the number of machines actually used. A bi-objective mixed-integer linear programming model is first formulated for the problem. An insertion algorithm is then proposed for the single-objective scheduling problem of minimizing the total electricity cost for a given number of machines. To obtain the whole Pareto front of the problem, an iterative search framework is developed based on the proposed insertion algorithm. Computational results on real-life and randomly generated instances demonstrate that the proposed approach is quite efficient and can find high-quality Pareto fronts for large-size problems with up to 5000 jobs.

关键词： bi-objective scheduling uniform parallel machines energy-efficient scheduling insertion algorithm time-of-use (TOU) electricity prices

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Research on Immune Genetic Algorithm for Solving bi-objective scheduling Problems Subjected to Special Process Constraint

Research on Immune Genetic Algorithm for Solving Bi-Objectiv...

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IEEE International Conference on Automation and Logistics

作者： Gao, Jiaquan He, Guixia Wang, Yushun Zhejiang Univ Technol Zhijiang Coll Hangzhou 310024 Zhejiang Peoples R China Nanjing Normal Univ Sch Math & Comp Sci Nanjing 210097 Jiangsu Peoples R China

ISBN: (纸本)9781424425020

The study presents a bi-objective scheduling model on parallel machines(BOSP), and proposes an immune genetic algorithm (VIGA) based on the vector group encoding method and the immune method. Compared with other scheduling problems on parallel machines, The BOSP is distinct for the following characteristics: (1) parallel machines are nonidentical;(2) the sort of jobs processed on every machine can be restricted;(3) take minimizing the total tardiness penalty and minimizing the total completion time into account as a bi-objective problem. For VIGA, its three distinct characteristics are described as follows. Firstly, individuals are represented by a vector group, which can effectively reflect the virtual scheduling policy;Secondly, an immune operator is adopted and studied in order to guarantee diversity of the population;Finally, a local search algorithm is applied to improve quality of the population. Numerical experiments show that it is efficient, and can better overcome drawbacks of the genetic algorithm proposed in [13]. A much better prospect of application can he optimistically expected.

关键词： bi-objective scheduling special process constraint parallel machines immune genetic algorithm

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bi-objective scheduling with cooperating heuristics for embedded real-time systems

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INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS 2020年第2期12卷 234-242页

作者： Bendib, Sonia Sabrina Kalla, Hamoudi Kalla, Salim Univ Batna 2 Dept Comp Sci LaSTIC Lab Batna Algeria

This paper proposes a makespan and reliability-based approach, a static scheduling strategy for distributed real-time embedded systems that aims to optimise the makespan and the reliability of an application. This scheduling problem is NP-hard and we rely on a heuristic algorithm to obtain efficiently approximate solutions. Two contributions have to be outlined: first, a hierarchical cooperation between heuristics ensuring to treat alternatively the objectives;and second, an adaptation module allowing improving solution exploration by extending the search space. The results are a set of compromising solutions offering the designer the possibility to make choices in line with his (her) needs. The method was tested and experimental results are provided.

关键词： embedded systems real-time systems cooperating heuristics bi-objective scheduling reliability Pareto front makespan multi-objective optimisation

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THE EFFECT OF WORKER LEARNING ON scheduling JOBS IN A HYBRID FLOW SHOP： A bi-objective APPROACH

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Journal of Systems Science and Systems Engineering 2018年第3期27卷 265-291页

作者： Farzad Pargar Mostafa Zandieh Osmo Kauppila Jaakko Kujala Industrial Engineering and Management Faculty of Technology University ofOulu Oulu Finland Department of Industrial Management Management and Accounting Faculty Shahid Beheshti University G.C.Tehran Iran

This paper studies learning effect as a resource utilization technique that can model improvement in worker＇s ability as a result of repeating similar tasks. By considering learning of workers while performing setup times, a schedule can be determined to place jobs that share similar tools and fixtures next to each other. The purpose of this paper is to schedule a set of jobs in a hybrid flow shop （HFS） environment with learning effect while minimizing two objectives that are in conflict： namely maximum completion time （makespan） and total tardiness. Minimizing makespan is desirable from an internal efficiency viewpoint, but may result in individual jobs being scheduled past their due date, causing customer dissatisfaction and penalty costs. A bi-objective mixed integer programming model is developed, and the complexity of the developed bi-objective model is compared against the bi-criteria one through numerical examples. The effect of worker learning on the structure of assigned jobs to machines and their sequences is analyzed. Two solution methods based on the hybrid water flow like algorithm and non-dominated sorting and ranking concepts are proposed to solve the problem. The quality of the approximated sets of Pareto solutions is evaluated using several performance criteria. The results show that the proposed algorithms with learning effect perform well in reducing setup times and eliminate the need for setups itself through proper scheduling.

关键词： bi-objective scheduling hybrid flow shop learning effect meta-heuristic

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bi-objective hybrid flow shop scheduling: a new local search

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第5-8期64卷 933-950页

作者： Mousavi, S. M. Mousakhani, M. Zandieh, M. Islamic Azad Univ Fac Ind Engn Dept Tech Engn Noshahr Branch Noshahr Iran Islamic Azad Univ Dept Business Management Fac Management & Econ Sci & Res Branch Tehran Iran Shahid Beheshti Univ Management & Accounting Fac Dept Ind Management GC Tehran Iran

In this paper, we have considered the bi-objective hybrid flow shop scheduling problem with the objectives of minimizing makespan and minimizing total tardiness. The problem is, however, a combinatorial optimization problem which is too difficult to be solved optimally, and hence, heuristics are used to obtain good solutions in a reasonable time. On the other hand, local search is a method for solving computationally hard optimization problems. Hence, we introduce a novel bi-objective local search algorithm (BOLS) to solve the problem efficiently. This local search can perform an effective search in three phases. In the initial phase, the assigned job set of a machine is moved to other machines. In the second phase, the order of jobs is changed for a machine. Finally, in phase 3, a process is done to change the assigned job set of a machine and order of jobs for a machine simultaneously. A measure of performance in literature namely free disposal hull approach and a new technique proposed by authors called "triangle method" have been used to evaluate the quality of the obtained solutions. The experimental results of the comparison between the proposed algorithm and several effective algorithms show that the BOLS is attractive for solving the bi-objective scheduling problem.

关键词： bi-objective scheduling Hybrid flow shop Free disposal hull approach Local search Triangle method

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Energy-efficient bi-objective single-machine scheduling with power-down mechanism

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COMPUTERS & OPERATIONS RESEARCH 2017年 85卷 172-183页

作者： Che, Ada Wu, Xueqi Peng, Jing Yan, Pengyu Northwestern Polytech Univ Sch Management Xian 710072 Peoples R China Univ Sci & Technol China Sch Management Hefei 230026 Peoples R China Univ Elect Sci & Technol China Sch Management & Econ Chengdu 610054 Peoples R China

This paper considers a single-machine scheduling, problem with power-down mechanism to minimize both total energy consumption and maximum tardiness. The aim is to find an optimal processing sequence of jobs and determine if the machine should be executed a power-down operation between two consecutive jobs. To formulate the problem, a mixed-integer linear programming (MILP) model is developed. Then a basic epsilon - constraint method is proposed to obtain the complete Pareto front of the problem. Considering the particularity of the problem, we also develop local search, preprocessing technique and valid inequalities to strengthen the basic epsilon - constraint method. Finally, to obtain approximate Pareto fronts for large-size problems, we utilize the method of cluster analysis to divide the jobs into several sorted clusters according to their release times and due dates. Any job in a preceding cluster must be processed before all jobs in a subsequent cluster. Thus, the solution space is reduced significantly. Computational experiments on benchmark and randomly generated instances demonstrate the effectiveness of the proposed exact and approximation approaches. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Energy-efficient scheduling Single machine bi-objective scheduling Power-down mechanism epsilon-constraint method

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bi-objective Operating Theater scheduling Case of the paediatric hospital of Oran 2

Bi-Objective Operating Theater Scheduling Case of the paedia...

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2nd IEEE International Conference on Logistics Operations Management (GOL)

作者： Dekhici, Latifa Belkadi, Khaled Univ Mohamed Boudiaf USTO MB Dept Comp Sci Fac Math & Comp Sci LAMOSI Lab Oran Algeria

ISBN: (纸本)9781479946501

In this paper, we propose a bi-objective Operating Theater scheduling subject to order and assignment constraints. The first objective is to minimize the total time operating theater opening or the makespan. The second is the maximum constraints satisfaction. The problem is a two stage hybrid flow shop with blocking. We compare the firefly algorithm, bats algorithm, particles swarm optimization and local search. In addition to the care specific quantitative and qualitative parameters, we use the average deviation from the lower bound to confirm the effectiveness of the methods. The implementation is done on the operating theater of the paediatric hospital of Oran when it is properly and improperly sized.

关键词： bi-objective scheduling hybrid flow shop with blocking constraint makespan firefly algorithm bat algorithm PSO operating theater

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bi-objective multi-mode resource-constrained multi-project scheduling using combined NSGA II and Q-learning algorithm*

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APPLIED SOFT COMPUTING 2024年 152卷

作者： Yang, Hongbing Wang, Ziyang Gao, Yue Zhou, Wei Soochow Univ Sch Mech & Elect Engn 8 Jixue Rd Suzhou 215137 Peoples R China

Multi -mode resource -constrained multi -project scheduling problem (MRCMPSP) plays a pivotal role in project management, serving as a critical component in production management for Engineering -to -Order manufacturing companies to enhance productivity, reduce costs, and minimize project completion time. This paper investigates the challenging problem of a bi-objective MRCMPSP, considering resource and finish time constraints, and develops a mathematical model to reduce project cycles and achieve better resource load balancing. By leveraging on the independent nature of start time selection for each activity, which aligns with the characteristics of a Markov decision process, we propose a two -layer iterative algorithm that combines the Nondominated Sorting Genetic Algorithm II (i.e., NSGA II) and Q -learning algorithm to solve the model effectively. Hence, the NSGA II algorithm generates mode combinations, while its fitness function employs the Qlearning algorithm to search for optimal activity time selections within each mode. We verify the performance superiority of the proposed algorithm by conducting a comparative analysis against classical approaches, encompassing classical NSGA II, Particle Swarm Optimization, and Ant Colony Optimization algorithms. Furthermore, this study's experimental results therefore unequivocally demonstrate the effectiveness of our algorithm in achieving optimized project scheduling outcomes.

关键词： MRCMPSP bi-objective scheduling NSGA II Q-learning Engineering-to-Order manufacturing

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A bi-objective Paediatric Operating Theater scheduling

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INTERNATIONAL JOURNAL OF HEALTHCARE INFORMATION SYSTEMS AND INFORMATICS 2023年第1期18卷

作者： Dekhici, Latifa Belkadi, Khaled Univ Sci & Technol Oran Mohamed Boudiaf Bir El Djir Algeria

In this paper, a bi-objective Operating Theater scheduling is proposed. The problem is subject to order and assignment constraints. The first objective is the minimization of the operating theater opening total time also called makespan in manufacturing systems while the second is to maximize constraints satisfaction. The scheduling problem is considered as a two-stage hybrid flow shop with blocking. Several metaheuristics are compared: the firefly algorithm, bats algorithm, particles swarm optimization and local search. In addition to the care specific qualitative and quantitative parameters, the average deviation from the lower bound is used in order to confirm the effectiveness of the methods. The implementation is done on the operating theater of the paediatric hospital of Oran when it is properly and improperly sized.

关键词： Bat Algorithm PSO bi-objective scheduling Constraint Hybrid Flow Shop With Blocking Makespan Firefly Algorithm Operating Theater

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A simulated annealing/local search to minimize the makespan and total tardiness on a hybrid flowshop

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第1-4期64卷 369-388页

作者： Mousavi, S. M. Zandieh, M. Yazdani, M. Islamic Azad Univ Fac Ind Engn Dept Tech & Engn Noshahr Iran Shahid Beheshti Univ Med Sci Management & Accounting Fac Dept Ind Management GC Tehran Iran Islamic Azad Univ Qazvin branch Fac Ind & Mech Engn Dept Ind Engn Qazvin Iran

scheduling is a major issue faced every day in manufacturing systems as well as in the service industry, so it is essential to develop effective and efficient advanced manufacturing and scheduling technologies and approaches. Also, it can be said that bi-criteria scheduling problems are classified in two general categories respecting the approach used to solve the problem. In one category, the aim is to determine a schedule that minimizes a convex combination of two objectives and in the other category is to find a good approximation of the set of efficient solutions. The aim of this paper is to determine a schedule for hybrid flowshop problem that minimizes a convex combination of the makespan and total tardiness. For the optimization problem, a meta-heuristic procedure is proposed based on the simulated annealing/local search (SA/LS) along with some basic improvement procedures. The performance of the proposed algorithm, SA/LS, is compared with a genetic algorithm which had been presented in the literature for hybrid flowshop with the objective of minimizing a convex combination of the makespan and the number of tardy jobs. Several computational tests are used to evaluate the effectiveness and efficiency of the proposed algorithm against the other algorithm provided in the literature. From the results obtained, it can be seen that the proposed algorithm in comparison with the other algorithm is more effective and efficient.

关键词： bi-objective scheduling Hybrid flowshop Simulated annealing Makespan Total tardiness

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