نتایج جستجو برای: quadratic earliness and tardiness
تعداد نتایج: 16835768 فیلتر نتایج به سال:
The just-in-time concept in manufacturing has aroused interest in machine scheduling problems with earliness-tardiness penalties. In particular, common due date problems, which are structurally less complicated than problems with general due dates, have emerged as an interesting and proliic eld of research. We prove that so-called almost common due date problems, in which the due date d j and p...
This paper employs an interactive possibility linear programming approach to solve a single machine scheduling problem with imprecise processing times, due dates, as well as earliness and tardiness penalties of jobs. The proposed approach is based on a strategy of minimizing the most possible value of the imprecise total costs, maximizing the possibility of obtaining a lower total costs, and mi...
This paper investigates common (slack) due-date assignment single-machine scheduling with controllable processing times within a group technology environment. Under linear and convex resource allocation functions, the cost function minimizes (including weighted sum of earliness, tardiness, assignment, where weights are position-dependent) resource-allocation costs. Given some optimal properties...
This paper investigates an unrelated parallel machine scheduling problem with a restrictive common due date. The objective is to minimize the total sum of earliness/tardiness costs. Using some properties such as V-Shaped property, optimizing start times machines, and no idle time between successive jobs, we propose effective construction-based heuristics local search algorithms for problem. var...
In this paper, we consider the slack due-window assignment model and study a single machine scheduling problem of linear time-dependent deteriorating jobs and a deteriorating maintenance activity. The cost for each job consists of four components: earliness, tardiness, window location and window size. The objective is to schedule the jobs and to assign the maintenance activity and due-windows s...
In the present work, an industrial case study has been considered for multi-objective flow shop scheduling problem including the sequence dependent set up time. The multi-objectives include the minimization of sum of total weighted squared tardiness, total weighted squared earliness, makespan and number of tardy jobs. Industries can select the optimal sequence with respect to required objective...
In this paper we study the problem of scheduling n deteriorating jobs on m identical parallel machines. Each job’s processing time is a nondecreasing function of its start time. The problem is to determine an optimal combination of the due-date and schedule so as to minimize the sum of the due-date, earliness and tardiness penalties. We show that this problem is NP-hard, and we present a heuris...
We address the problem of determining schedules for static, single-machine scheduling problems where the objective is to minimize the sum of weighted tardiness and weighted earliness. We develop optimal and heuristic procedures for the special case of weights that are proportional to the processing times of the respective jobs. The optimal procedure uses dominance properties to reduce the numbe...
This paper considers Just-In-Time Job-Shop Scheduling, in which each activity has an earliness and a tardiness cost with respect to a due date. It proposes a constraint programming approach, which includes a novel filtering algorithm and dedicated heuristics. The filtering algorithm uses a machine relaxation to produce a lower bound that can be obtained by solving a Just-In-Time Pert problem. I...
This paper considers a scheduling problem for minimizing the sum of the absolute deviations of completion times from the due dates of all jobs (earliness-tardiness) on a single batch processing machine. For this problem, each job has a corresponding processing time and size and all jobs have the common due date. The problem under study is NP-hard and hence a hybrid genetic algorithm based on a ...
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