Results 1  10
of
94
The hybrid flow shop scheduling problem
 European Journal of Operational Research
, 2010
"... The scheduling of flow shops with multiple parallel machines per stage, usually referred to as the Hybrid Flow Shop (HFS), is a complex combinatorial problem encountered in many real world applications. Given its importance and complexity, the HFS problem has been intensively studied. This paper pr ..."
Abstract

Cited by 16 (0 self)
 Add to MetaCart
(Show Context)
The scheduling of flow shops with multiple parallel machines per stage, usually referred to as the Hybrid Flow Shop (HFS), is a complex combinatorial problem encountered in many real world applications. Given its importance and complexity, the HFS problem has been intensively studied. This paper presents a literature review on exact, heuristic and metaheuristic methods that have been proposed for its solution. The paper discusses several variants of the HFS problem, each in turn considering different assumptions, constraints and objective functions. Research opportunities in HFS are also discussed. 1
Group Scheduling Problems In Flexible Flow Shops
 Proc. of the Annual Conference of Institute of Industrial Engineers
, 2002
"... Flexible flow shops are becoming increasingly common in industry practice because of higher workloads imposed by jobs on one or more stages, thus requiring two or more units of the same machine type. We present a methodology for solving this important problem, namely group scheduling, within the c ..."
Abstract

Cited by 6 (2 self)
 Add to MetaCart
Flexible flow shops are becoming increasingly common in industry practice because of higher workloads imposed by jobs on one or more stages, thus requiring two or more units of the same machine type. We present a methodology for solving this important problem, namely group scheduling, within the context of cellular manufacturing systems in order to minimize the total completion time of all groups of jobs considered in the planning horizon. Two different setup options, namely ############ and ###############, are investigated for jobs within the same group. A combined heuristic solution algorithm, comprised of single and multiplepass heuristics, is used for solving the problem. An example problem, consisting of three different problem instances of the same structure, is used to not only demonstrate the applicability of the solution algorithm, but also to identify the setup to ####### job run time ratios that should ###############prevail across all stages represented by two or more identical units in order to select ############### over ############ or vice versa. Keywords Group Scheduling; Flexible Flow Shops 1.
A Dynamic Heuristic for the Stochastic Unrelated Parallel Machine Scheduling Problem
 International Journal of Operations Research
, 2006
"... AbstractThis paper addresses the problem of batch scheduling in an unrelated parallel machine environment with sequence dependent setup times and an objective of minimizing the total weighted mean completion time. The jobs’ processing times and setup times are stochastic for better depiction of the ..."
Abstract

Cited by 4 (2 self)
 Add to MetaCart
(Show Context)
AbstractThis paper addresses the problem of batch scheduling in an unrelated parallel machine environment with sequence dependent setup times and an objective of minimizing the total weighted mean completion time. The jobs’ processing times and setup times are stochastic for better depiction of the real world. This is a NPhard problem and in this paper, new heuristics are developed and compared to existing ones using simulation. The results and analysis obtained from the computational experiments proved the superiority of the proposed algorithm PMWP over the other algorithms presented.
Synthesis of Fast Programs for Maximum Segment Sum Problems
"... It is wellknown that a naive algorithm can often be turned into an efficient program by applying appropriate semanticspreserving transformations. This technique has been used to derive programs to solve a variety of maximumsum programs. One problem with this approach is that each problem variation ..."
Abstract

Cited by 3 (2 self)
 Add to MetaCart
It is wellknown that a naive algorithm can often be turned into an efficient program by applying appropriate semanticspreserving transformations. This technique has been used to derive programs to solve a variety of maximumsum programs. One problem with this approach is that each problem variation requires a new set of transformations to be derived. An alternative approach to synthesis combines problem specifications with flexible algorithm theories to derive efficient algorithms. We show how this approach can be implemented in Haskell and applied to solve constraint satisfaction problems. We illustrate this technique by deriving programs for three varieties of maximumweightsum problem. The derivations of the different programs are similar, and the resulting programs are asymptotically faster in practice than the programs created by transformation. 1.
A survey of genetic algorithms for shop scheduling problems
 in: P. Siarry: Heuristics: Theory and Applications, Nova Science Publishers
, 2013
"... Genetic algorithms are a very popular heuristic which have been successfully applied to many optimization problems within the last 30 years. In this chapter, we give a survey on some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
(Show Context)
Genetic algorithms are a very popular heuristic which have been successfully applied to many optimization problems within the last 30 years. In this chapter, we give a survey on some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on a set of machines such that a specific optimization criterion is satisfied. According to the restrictions on the technological routes of the jobs, we distinguish a flow shop (each job is characterized by the same technological route), a job shop (each job has a specific route) and an open shop (no technological route is imposed on the jobs). We also consider some extensions of shop scheduling problems such as hybrid or flexible shops (at each processing stage, we may have a set of parallel machines) or the inclusion of additional processing constraints such as controllable processing times, release times, setup times or the nowait condition. After giving an introduction into basic genetic algorithms dis
On Performance Comparisons of GA, PSO and proposed Improved PSO for Job Scheduling in Multiprocessor Architecture
, 2011
"... Job Scheduling in a Multiprocessor architecture is an extremely difficult NP hard problem, because it requires a large combinatorial search space and also precedence constraints between the processes. For the effective utilization of multiprocessor system, efficient assignment and scheduling of jobs ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
(Show Context)
Job Scheduling in a Multiprocessor architecture is an extremely difficult NP hard problem, because it requires a large combinatorial search space and also precedence constraints between the processes. For the effective utilization of multiprocessor system, efficient assignment and scheduling of jobs is more important. This paper proposes a new improved Particle Swarm Optimization (ImPSO) algorithm for the job scheduling in multiprocessor architecture in order to reduce the waiting time and finishing time of the process under consideration. In the Improved PSO, the movement of a particle is governed by three behaviors, namely, inertia, cognitive, and social. The cognitive behavior helps the particle to remember its previous visited best position. This paper proposes to split the cognitive behavior into two sections.This modification helps the particle to search the target very effectively. The proposed ImPSO algorithm is discussed in detail and results are shown considering different number of processes and also the performance results are compared with the other heuristic optimization
Algorithms for a realistic variant of flowshop scheduling
"... This paper deals with a realistic variant of flowshop scheduling, namely the hybrid flexible flowshop. A hybrid flowshop mixes the characteristics of regular flowshops and parallel machine problems by considering stages with parallel machines instead of having one single machine per stage. We also i ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
This paper deals with a realistic variant of flowshop scheduling, namely the hybrid flexible flowshop. A hybrid flowshop mixes the characteristics of regular flowshops and parallel machine problems by considering stages with parallel machines instead of having one single machine per stage. We also investigate the flexible version where stage skipping might occur, i.e., not all stages must be visited by all jobs. Lastly, we also consider job sequence dependent setup times per stage. The optimization criterion considered is makespan minimization. The literature is plenty with approaches for hybrid flowshops. However, hybrid flexible flowshops have been seldom studied. The situation is even worse with the addition of sequence dependent setups. In this study, we propose two advanced algorithms that specifically deal with the flexible and setup characteristics of this problem. The first algorithm is a dynamic dispatching rule heuristic, and the second is an iterated local search metaheuristic. The proposed algorithms are evaluated by comparison against seven other high performing existing algorithms. The statistically sound results support the idea that the proposed algorithms are very competitive for the studied problem.
A hybrid tabu search heuristic for the twostage assembly scheduling problem
 International Journal of Operations Research
, 2006
"... AbstractIn this paper, we address the twostage assembly scheduling problem where there are m machines at the first stage and an assembly machine at the second stage. The objective is to schedule the jobs on the machines so that total completion time of all n jobs is minimized. Optimal solutions are ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
AbstractIn this paper, we address the twostage assembly scheduling problem where there are m machines at the first stage and an assembly machine at the second stage. The objective is to schedule the jobs on the machines so that total completion time of all n jobs is minimized. Optimal solutions are obtained for two special cases. A simulated annealing heuristic, a tabu search heuristic, and a hybrid tabu search heuristic are proposed for the general case. The proposed heuristics are compared with the existing heuristics and shown to be more efficient. The computational analysis shows that the proposed hybrid tabu search heuristic improves the error rate by about 60 and 90 percent over tabu search and simulated annealing heuristics, respectively, where the CPU time of all the three heuristics is almost the same.