جستجوی مقالات مرتبط با کلیدواژه « weighted tardiness » در نشریات گروه « صنایع »
تکرار جستجوی کلیدواژه «weighted tardiness» در نشریات گروه «فنی و مهندسی»-
This paper presents a bi-objective MIP model for the flexible flow shop scheduling problem (FFSP) in which the total weighted tardiness and the energy consumption are minimized simultaneously. In addition to considering unrelated machines at each stage, the set-up times are supposed to be sequence- and machine-dependent, and it is assumed that jobs have different release times. Two Taguchi-based-tuned algorithms: (i) non-dominated sorting genetic algorithm II (NSGA-II), and (ii) non-dominated ranked genetic algorithm (NRGA) are applied to solve themodel. Six numerical examples with different sizes (small, medium, and large) are used to demonstrate the applicability and to exhibit the efficacy of the algorithms. The results show that the NRGA outperforms significantly the NSGA-II in the performance metrics for all six numerical examples.Keywords: Flexible flow shop scheduling, energy consumption, weighted tardiness, Genetic Algorithm, strength Pareto evolutionary algorithm}
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Journal of Optimization in Industrial Engineering, Volume:9 Issue: 20, Summer and Autumn 2016, PP 19 -30Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters with it, this is why in recent decades extensive researches have been done on scheduling issues. A type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for appraising a multi-objective programing that minimize total weighted tardiness, earliness and total flowtime with fuzzy parameters on parallel machines, simultaneously with respect to the impact of machine deterioration. Besides, in this paper is attempted to present a defuzzification approach and a heuristic method based genetic algorithm (GA) to solve the proposed model. Finally, several dominance properties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver and the simulated annealing method that is followed by illustrating some instances for indicating validity and efficiency of the method.Keywords: Mathematical optimization, Fuzzy multi, objective model, Parallel machines scheduling, Weighted tardiness, earliness, Genetic Algorithm}
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Journal of Industrial Engineering and Management Studies, Volume:1 Issue: 1, Summer-Autumn 2014, PP 1 -19Make-to-order is a production strategy in which manufacturing starts only after a customer''s order is received; in other words, it is a pull-type supply chain operation since manufacturing is carried out as soon as the demand is confirmed. This paper studies the order acceptance problem with weighted tardiness penalties in permutation flow shop scheduling with MTO production strategy, the objective function of which is to maximize the total net profit of the accepted orders. The problem is formulated as an integer-programming (IP) model, and a cloud-based simulated annealing (CSA) algorithm is developed to solve the problem. Based on the number of candidate orders the firm receives, fifteen problems are generated. Each problem is regarded as an experiment, which is conducted five times to compare the efficiency of the proposed CSA algorithm to the one of simulated annealing (SA) algorithm previously suggested for the problem. The experimental results testify to the improvement in objective function values yielded by CSA algorithm in comparison with the ones produced by the formerly proposed SA algorithm.Keywords: Permutation flow shop scheduling, order acceptance, weighted tardiness, cloud, based simulated annealing algorithm, make, to, order production strategy}
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Journal of Optimization in Industrial Engineering, Volume:7 Issue: 14, Winter and Spring 2014, PP 61 -73Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. One type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for appraising a multi-objective programing that minimize total weighted tardiness, earliness and total flowtime with fuzzy parameters on parallel machines, simultaneously with respect to the impact of machine deterioration. Besides, in this paper attempted to present a defuzzification approach and a heuristic method based on genetic algorithm (GA) to solve the proposed model. Finally, several dominant properties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver and the simulated annealing method that is followed by illustrating some instances for indicating validity and efficiency of the method.Keywords: Mathematical optimization, Fuzzy multi, objective model, Parallel machines scheduling, Weighted tardiness, earliness, Genetic algorithm}
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طز آنجا که تعیین برنامه های زمانبندی کارا در مسائل توالی عملیات برای معیارهای مختلف، ازجمله مسائل مهم در برنامه ریزی تولید است، لذا در این مطالعه مساله توالی عملیات تک ماشینه با معیارهای حداقل کردن تعداد کارهای دارای تاخیر و مجموع دیرکرد موزون مورد بررسی قرار می گیرد. در این مقاله کاربرد روش های جدید بهینه سازی در مسائل توالی و زمانبندی مطرح می شود. ابتدا مدل ریاضی مساله برای اهداف موردنظر ارائه و سپس ضمن معرفی روش های شبیه سازی آنیلینگ و الگوریتم ژنتیک به عنوان روش های کاوشی، کارایی آنها در مساله موردنظر آزموده شده است. در پایان، جهت افزایش کارایی مدل الگوریتم ترکیبی برمبنای الگوریتم ژنتیک برای مساله ارائه شده است. این روش، مجموعه ای از توالی های کارا را به منظور حداقل کردن اهداف موردنظر مشخص می کندکلید واژگان: توالی عملیات تک ماشینه, برنامه ریزی چندهدفه, تاخیر, دیرکرد وزنی, الگوریتم های فراابتکاری}International Journal of Industrial Engineering & Production Management, Volume:24 Issue: 1, 2013, PP 1 -12Due to the fact that the determination of an efficient scheduling solution in the sequence of single machine operation for multiple objective programming is important, especially in production planning, we are considering a single machine sequencing problem with minimizing the number of the tasks with lateness and weighted tardiness. In this article, the application of new optimization methods in sequencing problem and scheduling are in order. We propose the mathematical model for the problem under consideration first and then by introducing simulated annealing and genetic algorithm, as solution approaches, we test their efficiency for solving the proposed problem. At the end, to increase the efficiency of the proposed model a hybrid/meta-heuristic algorithm based upon the genetic algorithm is proposed. This method identifies a collection of efficient sequencing tools for objectives minimization.Keywords: Sequence of Single Machine Operation, Multi Objective Programming, Lateness, Weighted Tardiness, Meta, Heuristic}
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