نتایج جستجو برای: total earliness and tardiness
تعداد نتایج: 16875967 فیلتر نتایج به سال:
In this paper, a scheduling problem for multiple automated guided vehicles (AGVs) in a manufacturing system is proposed and formulated. Considering the due date of AGVs requiring for material handling among shops in a jobshop layout, their earliness and tardiness are significant in satisfying the expected cycle time and from an economic view point. Earliness results in AGVs waiting and tardines...
This paper considers the problem of linding an optimal schedule and a common due date for a set of jobs, in a static single machine system. The scheduling criterion is the minimization of the weighted sum of earliness and tardiness values. Different weights are considered as the earliness penalty and tardiness penalty, for each job. A branching procedure is presented for finding an optimal solu...
This study proposes an exact algorithm for the precedence-constrained singlemachine scheduling problem to minimize total job completion cost where machine idle time is forbidden. The proposed algorithm is an extension of the authors’ previous algorithms for the problem without precedence-constraints and is based on the SSDP (Successive Sublimation Dynamic Programming) method. Numerical experime...
Single machine, distinct due dates, early/lately machine problem and fuzzy environment closely models the situation faced by ‘Just In Time’ manufacturing. The objective of this paper is to sequence the jobs on the machine, so that the total penalty cost be minimum. This cost is composed of the total earliness and the total tardiness cost. An algorithm is developed here to minimize the total pen...
We study a common due-date assignment problem on two parallel uniform machines. The jobs are assumed to have identical processing times, and job-dependent asymmetric earliness tardiness unit costs. scheduler may process only subset of the jobs, i.e. option job-rejection is allowed. objective function consists three cost components: total earliness-tardiness all scheduled due-date, rejection cos...
Focusing on the just-in-time (JIT) operations management, earliness as well as, tardiness of jobs’ production and delivery should be discouraged. In accordance to this philosophy, scheduling problems involving earliness and tardiness penalties are very critical for the operations manager. In this paper, a new population heuristic based on the particle swarm optimization (PSO) technique is prese...
In this paper, we consider a machine scheduling problem where jobs should be completed at times as close as possible to their respective due dates, and hence both earliness and tardiness should be penalized. Specifically, we consider the problem with a set of independent jobs to be processed on several identical parallel machines. All the jobs have a given common due window. If a job is complet...
in this paper, a single machine sequencing problem is considered in order to find the sequence of jobs minimizing the sum of the maximum earliness and tardiness with idle times (n/1/i/etmax). due to the time complexity function, this sequencing problem belongs to a class of np-hard ones. thus, a special design of a simulated annealing (sa) method is applied to solve such a hard problem. to comp...
This study addresses a class of single-machine scheduling problems involving a common due date where the objective is to minimize the total job earliness and tardiness penalties. A genetic algorithm (GA) approach and a simulated annealing (SA) approach utilizing a greedy local search and three well-known properties in the area of common due date scheduling are developed. The developed algorithm...
The single-machine early/tardy (E/T) scheduling problem is addressed in this research. The objective of this problem is to minimize the total amount of earliness and tardiness. Earliness and tardiness are weighted equally and the due date is common and large (unrestricted) for all jobs. Machine setup time is included and is considered sequence-dependent. When sequence-dependent setup times are ...
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