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This paper focuses on the flow shop sequence dependent group scheduling (FSDGS) problem with minimisation of total completion time as the criterion (Fm|f mls, prmu, S plk|ΣC j). The research problem is formulated in form of two different mixed integer linear programming (MILP) models. Comparing with the latest MILP model for the proposed problem in the literature, the complexity size of the proposed models are significantly reduced. One of the proposed mathematical models is so effective that even medium-sized instances (problems up to 60 jobs in all groups) are solved to optimality in a reasonable amount of time. Moreover, a metaheuristic hybridising genetic and simulated annealing... 

In this paper a lower bounding method for the flowshop sequence dependentgroups scheduling problems by minimization of makespan criterion (Fm|fmls, Sijkprmu|Cmax) is proposed. Theperformance of the proposed lower bound (LB) is compared with the availablelower bounding methods in literature. In order to do this, the performance ofthe proposed LB and the one available in literature are compared with theavailable upper bound in literature based on solving the available testproblems. The results show that the proposed LB has a superior performancecompared to the available ones in literature. The average percentage error ofthe proposed LB for the test problems is 1.1% and 1.4% for three and six... 

This research considers a flexible flowshop sequence-dependent group scheduling problem with minimization of total completion time. A mixed integer linear mathematical model for the research problem is developed. Since the research problem is shown to be strongly NP-hard, a metaheuristic algorithm based on memetic algorithm (MA) is proposed. A lower bounding method based on the Branch and Price algorithm is also proposed to evaluate the quality of the MA. In order to evaluate the performance of the proposed algorithms, random test problems, ranging in size from small, medium, to large are generated and solved by the MA and the lower bounding method. The results show that the average... 

A Particle Swarm Optimization (PSO) algorithm for a Flow Shop Sequence Dependent Group Scheduling (FSDGS) problem, with minimization of total flow time as the criterion (Fmmls, Spuc, prmu 52 Q), is proposed in this research. An encoding scheme based on Ranked Order Value (ROV) is developed, which converts the continuous position value of particles in PSO to job and group permutations. A neighborhood search strategy, called Individual Enhancement (IE), is fused to enhance the search and to balance the exploration and exploitation. The performance of the algorithm is compared with the best available meta-heuristic algorithm in literature, i.e. the Ant Colony Optimization (ACO) algorithm, based... 

The focus of this research is on the flexible flow shop sequence dependent group scheduling problem (FFSDGS) with minimization of makespan as the criterion (FFm|fmls, Splk|Cmax). Since the research problem is shown to be NP-hard, a meta-heuristic algorithms based on memetic algorithm is developed to efficiently solve the problem. The performance of the proposed algorithm is compared with the only available meta-heuristic algorithm in the literature, i.e., tabu search (TS). The comparison is performed based on paired t-test and the result shows that the memetic algorithm has a superior performance compared to the TS  

In this research, the no-wait flowshop sequence dependent group scheduling problem with minimisation of total completion time, noted as Fm|nwt, fmls, Splk|∑Cj is approached. A mixed integer linear mathematical model is proposed for the research problem. Due to the NP-hard nature of the proposed problem, several metaheuristic algorithms based on particle swarm optimisation and variable neighbourhood search with different neighbourhood search structures are proposed to heuristically solve the problem. Also, an efficient heuristic algorithm is proposed to generate the initial feasible solutions for the proposed algorithms. The performances of the proposed algorithms are compared with each other... 

A bicriteria two-machine flowshop scheduling problem is addressed to minimize the number of setups and makespan. The jobs have sequence dependent setup times. Scheduling problems considering either of these objectives are NP-hard. Two multi-objective metaheurisctics based on genetic algorithms (MOGA) and simulated annealing (MOSA) are proposed to find approximations of Pareto-optimal frontiers. The performances of these approaches are compared with lower bounds for small problems. In larger problems, their performance is compared with each other. Experimentations revealed that both algorithms perform very similar on small problems and that MOGA outperforms MOSA in terms of the quality of... 

A two-machine flowshop scheduling problem is addressed to minimize setups and makespan where each job is characterized by a pair of attributes that entail setups on each machine. The setup times are sequence-dependent on both machines. It is shown that these objectives conflict, so the Pareto optimization approach is considered. The scheduling problems considering either of these objectives are N p - hard, so exact optimization techniques are impractical for large-sized problems. We propose two multi-objective metaheurisctics based on genetic algorithms (MOGA) and simulated annealing (MOSA) to find approximations of Pareto-optimal sets. The performances of these approaches are compared with... 

In this research, a permutation flowshop sequence-dependent group scheduling problem with minimisation of total completion time is considered. Since the problem is shown to be strongly NP-hard, a hybrid genetic (HG) algorithm is proposed. The only available lower bounding (LB) method for the proposed research problem in the literature based on branch and price (B&P) algorithm is also enhanced by proposing efficient method to solve sub-problems and proposing a better branching rule. A statistical comparison shows that both the proposed HG algorithm and the proposed LB have better performance than the other methods from the literature with an average 5.96% percentage gap. [Received 13 December... 

In this research, we approach the flowshop sequence-dependent group scheduling problem with minimisation of total weighted earliness and tardiness as the objective for the first time. A mixed integer linear programming model is developed to solve the problem optimally. Since the proposed research problem is proven to be NP-hard, a hybrid meta-heuristic algorithm based on the particle swarm optimisation (PSO) algorithm, enhanced with neighbourhood search is developed to heuristically solve the problem. Since the objective is a non-regular, a timing algorithm is developed to find the best schedule for each sequence provided by the metaheuristic algorithm. A lower bounding method is also... 

In this research, the no-wait flowshop sequence-dependent setup time scheduling problem with minimization of weighted earliness and tardiness penalties as the criterion, typically classified as Fm|nwt, S ijk|∑wj'Ej+wj ″Tj, is investigated. A mixed integer linear programming model for the research problem is proposed. As the problem is shown to be strongly NP-hard, several metaheuristic algorithms based on tabu search (TS) and particle swarm optimization (PSO) algorithms are developed to heuristically solve the problem. A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence. In order to compare the performance of the... 

Flow shop scheduling problems with sequence-dependent setup times and minimising the number of tardy jobs as the criterion (F m |prmu, S ijk |∑U j) are considered in this research. A mixed-integer linear programming model is developed for the research problem. Since the proposed research problem has been proven to be NP-hard, several meta-heuristic algorithms based on tabu search (TS) and the imperialist competitive algorithm (ICA) are proposed to heuristically solve the problem. In order to find the best meta-heuristic algorithm, random test problems, ranging in size from small, medium, to large, are generated and solved by the meta-heuristic algorithms. Then, a detailed statistical... 

In this paper, the flexible flow shop sequence-dependent group scheduling problem (FFSDGS) with minimisation of makespan as the criterion (FF m|fmls, S plk|C max) is investigated. For the first time a mathematical model for the proposed research problem is developed. Since the problem is shown to be NP-hard, six metaheuristic algorithms based on tabu search (TS) are developed to efficiently solve the problem. The proposed metaheuristics are different to the only available metaheuristic algorithm in the literature based on TS. By applying randomised complete block design and using available test problems in the literature, the best of the proposed TS algorithms in this research is identified.... 

We are concerned with an open shop scheduling problem having sequence-dependent setup times. A novel bi-objective possibilistic mixed-integer linear programming model is presented. Sequence-dependent setup times, fuzzy processing times and fuzzy due dates with triangular possibility distributions are the main constraints of this model. An open shop scheduling problem with these considerations is close to the real production scheduling conditions. The objective functions are to minimize total weighted tardiness and total weighted completion times. To solve small-sized instances for Pareto-optimal solutions, an interactive fuzzy multi-objective decision making (FMODM) approach, called TH... 

This paper investigates permutation flow shop scheduling problems with sequencedependent setup times with minimizing the number of tardy jobs as criterion (F m|prmu, S ijk|σU j). Since the proposed research problem has been proven to be NP-hard, three different meta heuristic algorithms based on tabu search (TS) has been proposed to solve the problem. These three algorithms are different based on their tabu list characteristics. In order to evaluate the performance of the proposed TS algorithms, test problems in different ranges are generated to find the best algorithm. The comparison shows that the TS algorithm which its tabu list keeps track of the slots that the jobs are assigned has a... 

The flowshop sequence dependent group scheduling problem with minimization of makespan as the objective (F m |fmls, S plk, prmu|C max ) is considered in this paper. It is assumed that several groups with different number of jobs are assigned to a flow shop cell that has m machines. The goal is to find the best sequence of processing the jobs in each group and the groups themselves with minimization of makespan as the objective. A mathematical model for the research problem is developed in this paper. As the research problem is shown to be NP-hard, a hybrid ant colony optimization (HACO) algorithm is developed to solve the problem. A lower bounding technique based on relaxing a few...