This paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable m...

Batch processing becomes more important in the process industries, because of the increasing product variety and the decreasing demand volumes for individual products. In batch process industries it is difficult to predict the completion time, or makespan, of a set of jobs, because jobs interact at the shop floor. In this paper, we compare two different methods for predicting the makespan of jo...

The problem of nonpreemptively scheduling a set of rn partially ordered tasks on n identical processors subject to interprocessor communication delays is studied in an effort to minimize the makespan. A new heuristic, called Earliest Task First (ETF), is designed and analyzed. It is shown that the makespan wEx-generated by ETF always satisfies to Eq.. (2 1/n wopti) + C, where Wopti) is the opti...

We study temperature-aware scheduling problems under the model introduced by Chrobak et al. in [6]. We consider a set of parallel identical processors and three optimization criteria: makespan, maximum temperature and (weighted) average temperature. On the positive side, we present polynomial time approximation algorithms for the minimization of the makespan and the maximum temperature, as well...

In the context of Scheduling under uncertainty, Partial Order Schedules (POS) provide a convenient way to build flexible solutions. A POS is obtained from a Project Graph by adding precedence constraints so that no resource conflict can arise, for any possible assignment of the activity durations. In this paper, we use a simulation approach to evaluate the expected makespan of a number of POSs,...

current research addresses finding robust and stable schedule for the flexible job shop problem under machine breakdown. we have used simulation to investigate the effect of machine breakdown. two-stage of metaheuristic algorithm is developed to generate robust and stable schedule and is integrated with simulation algorithm. because makespan is primitive objective of every scheduling problem, i...

In this paper, a particle swarm optimization algorithm (PSO) is presented to solve the permutaion flowshop sequencing problem (PFSP) with the objectives of minimizing makespan and maximum lateness of jobs, respectively. Simple but very efficient local search based on variable neighborhood search (VNS) is embedded in the particle swarm optimization algorithm to solve the well known benchmark sui...

This paper pertains to a two machine flowshop scheduling involving independent setup time, transportation time and job block criteria in fuzzy environment. Further, a single transporting agent which carries the jobs from one machine to another is also considered. The objective of the paper is to minimize the makespan, idle time of the machines whenever the processing time, setup time each are u...

We consider the makespan minimization parallel machine scheduling problemwhere each machine may be unavailable for a known time interval. For this problem, we investigate how the worst-case behavior of the longest processing timefirst algorithm (LPT) is affected by the availability ofmachines. In particular, for givenmmachines, we analyze the cases where arbitrary number, , ranging from one tom...

In the multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple agents. Recently, existing makespan optimal SAT-based solvers for MAPF have been modified for the sum-of-costs objective. In this paper, we empirically compare the hardness of solving MAPF with SATbased and search-based solvers under the makespan and the sum-of-costs objectives in a number of domains. ...