Decomposition-based classified ant colony optimization algorithm for scheduling semiconductor wafer fabrication system
نویسندگان
چکیده
Due to its typical features, such as large-scale, multiple re-entrant flows, and hybrid machine types, the semiconductor wafer fabrication system (SWFS) is extremely difficult to schedule. In order to cope with this difficulty, the decomposition-based classified ant colony optimization (D-CACO) method is proposed and analyzed in this paper. The D-CACO method comprises decomposition procedure and classified ant colony optimization algorithm. In the decomposition procedure, a large and complicate scheduling problem is decomposed into several subproblems and these subproblems are scheduled in sequence. The classified ACO algorithm then groups all of the operations of the subproblems and schedules them according to machine type. To test the effect of the method, a set of simulations are conducted on a virtual fab simulation platform. The test results show that the proposed D-CACO algorithm works efficiently in sched-
منابع مشابه
Ant Colony Optimization Approaches for Scheduling Jobs with Incompatible Families on Parallel Batch Machines
In this paper, we suggest an Ant Colony System (ACS) to solve a scheduling problem for jobs with incompatible families on parallel batch machines. We are interested in minimizing total weighted tardiness (TWT) of the jobs. Problems of this type have practical importance in semiconductor manufacturing. The ACS scheme includes an efficient local search technique based on swapping jobs across diff...
متن کاملResource leveling scheduling by an ant colony-based model
In project scheduling, many problems can arise when resource fluctuations are beyond acceptable limits. To overcome this, mathematical techniques have been developed for leveling resources. However, these produce a hard and inflexible approach in scheduling projects. The authors propose a simple resource leveling approach that can be used in scheduling projects with multi-mode execution activit...
متن کاملDevelopment of a Multiobjective Scheduler for Semiconductor Manufacturing
Scheduling of semiconductor wafer fabrication system is identified as a complex problem, involving multiple and conflicting objectives (meeting due dates and minimizing waiting time for instance) to satisfy. In this study, we propose an effective approach based an artificial neural network technique embedded in a multiobjective optimization loop for multi-decision scheduling problems in a semic...
متن کاملNew Ant Colony Algorithm Method based on Mutation for FPGA Placement Problem
Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optim...
متن کاملNew Heuristic Function in Ant Colony System for Job Scheduling in Grid Computing
Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem. Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms. Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve differenttypes of NP-hard problems.However, ant colony s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Computers & Industrial Engineering
دوره 62 شماره
صفحات -
تاریخ انتشار 2012