Results 1 
7 of
7
A Survey of Scheduling Problems with Setup Times or Costs
"... The first comprehensive survey paper on scheduling problems with separate setup times or costs was conducted by Allahverdi et al. (1999), who reviewed the literature since the mid1960s. Since the appearance of that survey paper, there has been an increasing interest in scheduling problems with setu ..."
Abstract

Cited by 104 (5 self)
 Add to MetaCart
The first comprehensive survey paper on scheduling problems with separate setup times or costs was conducted by Allahverdi et al. (1999), who reviewed the literature since the mid1960s. Since the appearance of that survey paper, there has been an increasing interest in scheduling problems with setup times (costs) with an average of more than 40 papers per year being added to the literature. The objective of this paper is to provide an extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers. Given that so many papers have appeared in a short time, there are cases where different researchers addressed the same problem independently, and sometimes by using even the same technique, e.g., genetic algorithm. Throughout the paper we identify such areas where independently developed techniques need to be compared. The paper classifies scheduling problems into those with batching and nonbatching considerations, and with sequenceindependent and sequencedependent setup times. It further categorizes the literature according to shop environments, including singlemachine, parallel machines, flow shop, nowait flow shop, flexible flow shop, job shop, open shop, and others.
Dynamic Programming Approach to a Two Machine Flow Shop Sequencing with TwoStepPriorJob Dependent Setup Times
, 2006
"... Abstract. The purpose of this study is to develop an effective scheduling methodology for a realistic flow shop sequencing problem. The flow shop consists of two machines where only the first machine has separable, external, and sequence dependent setup times. The length of setup times required for ..."
Abstract
 Add to MetaCart
Abstract. The purpose of this study is to develop an effective scheduling methodology for a realistic flow shop sequencing problem. The flow shop consists of two machines where only the first machine has separable, external, and sequence dependent setup times. The length of setup times required for a job depends not on the immediately preceding job but on the job which is two steps prior to it. The problem is solved by a backward dynamic programming with the objective of minimizing the makespan. An optimal schedule is found and its performance is examined through a simulation study.
A Comparative Study of Twophase Heuristic Approaches to General Job Shop Scheduling Problem
"... Abstract. Scheduling is one of the most important issues in the planning and operation of production systems. This paper investigates a general job shop scheduling problem with reentrant work flows and sequence dependent setup times. The disjunctive graph representation is used to capture the intera ..."
Abstract
 Add to MetaCart
Abstract. Scheduling is one of the most important issues in the planning and operation of production systems. This paper investigates a general job shop scheduling problem with reentrant work flows and sequence dependent setup times. The disjunctive graph representation is used to capture the interactions between machines in job shop. Based on this representation, four twophase heuristic procedures are proposed to obtain near optimal solutions for this problem. The obtained solutions in the first phase are substantially improved by reversing the direction of some critical disjunctive arcs of the graph in the second phase. A comparative study is conducted to examine the performance of these proposed algorithms.
THE NOWAIT FLOWSHOP PROBLEM WITH SEQUENCE DEPENDENT SETUP TIMES AND RELEASE DATES
"... Population based metaheuristics, such as hybrid genetic algorithms or memetic algorithms, play an important role in the solution of combinatorial optimization problems. The memetic algorithm presented here for the nowait flowshop scheduling problem addresses a hierarchically organized complete tern ..."
Abstract
 Add to MetaCart
Population based metaheuristics, such as hybrid genetic algorithms or memetic algorithms, play an important role in the solution of combinatorial optimization problems. The memetic algorithm presented here for the nowait flowshop scheduling problem addresses a hierarchically organized complete ternary tree to represent the population that putted together with a recombination plan resembles a parallel processing scheme for solving combinatorial optimization problems. We propose a novel recursive local search scheme Recursive Arc Insertion (RAI) which is responsible for about 90 % of the total processing time of the algorithm. Randomly generated instances are used to test the algorithm against other proposed methods.
by
, 2009
"... In this research, a particle swarm optimization algorithm (PSO) using random keys is developed to schedule flexible flow lines with sequence dependent setup times to minimize makespan. The flexible flow line scheduling problem is a branch of production scheduling and is found in industries such as p ..."
Abstract
 Add to MetaCart
(Show Context)
In this research, a particle swarm optimization algorithm (PSO) using random keys is developed to schedule flexible flow lines with sequence dependent setup times to minimize makespan. The flexible flow line scheduling problem is a branch of production scheduling and is found in industries such as printed circuit board and automobile manufacturing. It is well known that this problem is NPhard. For this reason, we approach the problem by implementing a particle swarm optimization (PSO), a metaheuristic which is inspired by the motion of a flock of birds or a school of fish searching for food. The proposed PSO has many features, such as the use of random keys for encoding the solution, “bounceback ” of particles into the solution space and tuning of learning and weighting factors. The proposed PSO algorithm is implemented in C and tested on a large set of data found in the literature. Extensive computational experiments are facilitated through the use of highthroughput computing via Clemson’s Condor grid. The solution qualities are compared and evaluated with the help of lower bound developed by Kurz and Askin [16]. Unfortunately, we conclude that the proposed PSO
unknown title
"... Contents lists available at GrowingScience International Journal of Industrial Engineering Computations ..."
Abstract
 Add to MetaCart
Contents lists available at GrowingScience International Journal of Industrial Engineering Computations