Two-machine flowshop scheduling with flexible operations and controllable processing times

Ankara : The Department of Industrial Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.Thesis (Master's) -- Bilkent University, 2011.Includes bibliographical references leaves 77-84.In this study, we consider a two-machine flowshop scheduling problem with identical jobs. Each of these jobs has three operations, where the first operation must be performed on the first machine, the second operation must be performed on the second machine, and the third operation (named as flexible operation) can be performed on either machine but cannot be preempted. Highly flexible CNC machines are capable of performing different operations as long as the required cutting tools are loaded on these machines. The processing times on these machines can be changed easily in albeit of higher manufacturing cost by adjusting the machining parameters like the speed of the machine, feed rate, and/or the depth of cut. The overall problem is to determine the assignment of the flexible operations to the machines and processing times for each job simultaneously, with the bicriteria objective of minimizing the manufacturing cost and minimizing makespan. For such a bicriteria problem, there is no unique optimum but a set of nondominated solutions. Using ǫ constraint approach, the problem could be transformed to be minimizing total manufacturing cost objective for a given upper limit on the makespan objective. The resulting single criteria problem is a nonlinear mixed integer formulation. For the cases where the exact algorithm may not be efficient in terms of computation time, we propose an efficient approximation algorithm.Uruk, ZeynepM.S

Scheduling Jobs in Flowshops with the Introduction of Additional Machines in the Future

This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/expert-systems-with-applications/.The problem of scheduling jobs to minimize total weighted tardiness in flowshops,\ud with the possibility of evolving into hybrid flowshops in the future, is investigated in\ud this paper. As this research is guided by a real problem in industry, the flowshop\ud considered has considerable flexibility, which stimulated the development of an\ud innovative methodology for this research. Each stage of the flowshop currently has\ud one or several identical machines. However, the manufacturing company is planning\ud to introduce additional machines with different capabilities in different stages in the\ud near future. Thus, the algorithm proposed and developed for the problem is not only\ud capable of solving the current flow line configuration but also the potential new\ud configurations that may result in the future. A meta-heuristic search algorithm based\ud on Tabu search is developed to solve this NP-hard, industry-guided problem. Six\ud different initial solution finding mechanisms are proposed. A carefully planned\ud nested split-plot design is performed to test the significance of different factors and\ud their impact on the performance of the different algorithms. To the best of our\ud knowledge, this research is the first of its kind that attempts to solve an industry-guided\ud problem with the concern for future developments

Heuristics for scheduling a two-stage hybrid flow shop with parallel batching machines: application at a hospital sterilisation plant

The model of a two-stage hybrid (or flexible) flow shop, with sequence-independent uniform setup times, parallel batching machines and parallel batches has been analysed with the purpose of reducing the number of tardy jobs and the makespan in a sterilisation plant. Jobs are processed in parallel batches by multiple identical parallel machines. Manual operations preceding each of the two stages have been dealt with as machine setup with standardised times and are sequence-independent. A mixed-integer model is proposed. Two heuristics have been tested on real benchmark data from an existing sterilisation plant: constrained size of parallel batches and fixed time slots. Computation experiments performed on combinations of machines and operator numbers suggest balancing the two stages by assigning operators proportionally to the setup time requirements

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Serial-batch scheduling – the special case of laser-cutting machines

The dissertation deals with a problem in the field of short-term production planning, namely the scheduling of laser-cutting machines. The object of decision is the grouping of production orders (batching) and the sequencing of these order groups on one or more machines (scheduling). This problem is also known in the literature as "batch scheduling problem" and belongs to the class of combinatorial optimization problems due to the interdependencies between the batching and the scheduling decisions. The concepts and methods used are mainly from production planning, operations research and machine learning

Efficient heuristics for the parallel blocking flow shop scheduling problem

We consider the NP-hard problem of scheduling n jobs in F identical parallel flow shops, each consisting of a series of m machines, and doing so with a blocking constraint. The applied criterion is to minimize the makespan, i.e., the maximum completion time of all the jobs in F flow shops (lines). The Parallel Flow Shop Scheduling Problem (PFSP) is conceptually similar to another problem known in the literature as the Distributed Permutation Flow Shop Scheduling Problem (DPFSP), which allows modeling the scheduling process in companies with more than one factory, each factory with a flow shop configuration. Therefore, the proposed methods can solve the scheduling problem under the blocking constraint in both situations, which, to the best of our knowledge, has not been studied previously. In this paper, we propose a mathematical model along with some constructive and improvement heuristics to solve the parallel blocking flow shop problem (PBFSP) and thus minimize the maximum completion time among lines. The proposed constructive procedures use two approaches that are totally different from those proposed in the literature. These methods are used as initial solution procedures of an iterated local search (ILS) and an iterated greedy algorithm (IGA), both of which are combined with a variable neighborhood search (VNS). The proposed constructive procedure and the improved methods take into account the characteristics of the problem. The computational evaluation demonstrates that both of them –especially the IGA– perform considerably better than those algorithms adapted from the DPFSP literature.Peer ReviewedPostprint (author's final draft

An iterated greedy heuristic for no-wait flow shops with sequence dependent setup times, learning and forgetting effects

[EN] This paper addresses a sequence dependent setup times no-wait flowshop with learning and forgetting effects to minimize total flowtime. This problem is NP-hard and has never been considered before. A position-based learning and forgetting effects model is constructed. Processing times of operations change with the positions of corresponding jobs in a schedule. Objective increment properties are deduced and based on them three accelerated neighbourhood construction heuristics are presented. Because of the simplicity and excellent performance shown in flowshop scheduling problems, an iterated greedy heuristic is proposed. The proposed iterated greedy algorithm is compared with some existing algorithms for related problems on benchmark instances. Comprehensive computational and statistical tests show that the presented method obtains the best performance among the compared methods. (C) 2018 Elsevier Inc. All rights reserved.This work is supported by the National Natural Science Foundation of China (Nos. 61572127, 61272377), the Collaborative Innovation Center of Wireless Communications Technology and the Key Natural Science Fund for Colleges and Universities in Jiangsu Province (No. 12KJA630001). Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness(MINECO), under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards" with reference DPI2015-65895-R.Li, X.; Yang, Z.; Ruiz García, R.; Chen, T.; Sui, S. (2018). An iterated greedy heuristic for no-wait flow shops with sequence dependent setup times, learning and forgetting effects. Information Sciences. 453:408-425. https://doi.org/10.1016/j.ins.2018.04.038S40842545

Heuristic Approach to Job Scheduling in a Small Scale Groundnut Oil Processing Firm in Nigeria

Groundnut is an important legume cash crop for tropical farmers and its seeds contain high amounts of edible oil (43-55%) and protein (25-28%). This paper developed a framework for the scheduling of activities (jobs) in small scale groundnut oil processing firm in Nigeria. The research problem is addressed using makespan as a measure of performance with CDS, A1 and Usual Serial Order (USO) heuristics solution methods. Findings reveal that A1 and CDS heuristics are preferred to the traditional USO methods. Also, the mean of A1 (27.11) heuristic, followed by CDS (27.22) heuristics, gives the best makespan results while the USO (31.52) gives the worst result. This paper thus presents a framework that could be beneficial to stakeholders in the Groundnut oil processing industry towards improved customer’s satisfaction, less idle time, and profit optimization. Keywords: Groundnut, small enterprises, scheduling of orders, makespans, optimum results

An analysis of pure robotic cycles

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 20068Includes bibliographical references leaves 84-87.This thesis is focused on scheduling problems in robotic cells consisting of a number of CNC machines producing identical parts. We consider two different cell layouts which are in-line robotic cells and robot centered cells. The problem is to find the robot move sequence and processing times on machines minimizing the total manufacturing cost and cycle time simultaneously. The automation in manufacturing industry increased the flexibility, however it is not widely studied in the literature. The flexibility of machines enables us to process all the required operations for a part on the same machine. Furthermore, the processing times on CNC machines can be increased or decreased by changing the feed rate and cutting speed. Hence, we assume that a part is processed on one of the machines and the processing times are assumed to be controllable. The flexibility of machines results in a new class of cycles named pure cycles. We determined efficient pure cycles and corresponding processing times dominating the rest of pure cycles in the specified cycle time regions. In addition, for in-line robotic cells, the optimum number of machines is determined for given parameters.Yıldız, SerdarM.S