Flowshop scheduling problems with due date related objectives: A review of the literature

3rd International Conference on Industrial Engineering and Industrial Management XIII Congreso de Ingeniería de Organización Barcelona-Terrassa, September 2nd-4th 200

Multicriteria hybrid flow shop scheduling problem: literature review, analysis, and future research

This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future researchon this topic, including the following: (i) use uniform and dedicated parallel machines, (ii) use exact and metaheuristics approaches, (iv) develop lower and uppers bounds, relations of dominance and different search strategiesto improve the computational time of the exact methods,  (v) develop  other types of metaheuristic, (vi) work with anticipatory setups, and (vii) add constraints faced by the production systems itself

Project network models with discounted cash flows. A guided tour through recent developments.

The vast majority of the project scheduling methodologies presented in the literature have been developed with the objective of minimizing the project duration subject to precedence and other constraints. In doing so, the financial aspects of project management are largely ignored. Recent efforts have taken into account discounted cash flow and have focused on the maximalization of the net present value (npv) of the project as the more appropriate objective. In this paper we offer a guided tour through the important recent developments in the expanding field of research on deterministic and stochastic project network models with discounted cash flows. Subsequent to a close examination of the rationale behind the npv objective, we offer a taxonomy of the problems studied in the literature and critically review the major contributions. Proper attention is given to npv maximization models for the unconstrained scheduling problem with known cash flows, optimal and suboptimal scheduling procedures with various types of resource constraints, and the problem of determining both the timing and amount of payments.Scheduling; Models; Model; Discounted cash flow; Cash flow; Project scheduling; Project management; Management; Net present value; Value; Problems; Maximization; Optimal;

Using Branch and Bound Method to Minimize Bi-Criteria

This paper presents a branch and bound algorithm for sequencing a set of n independent jobs on a single machine to minimize sum of total late work and the number of tardy jobs, the type of the problem is NP-hard.Lower bounds were proposed and heuristic method to get an upper bound. Some special cases were proved and some dominancerules were proposed and proved, the problem solved with up to 40 jobs

An estimation of distribution algorithm for lot-streaming flow shop problems with setup times

Lot-streaming flow shops have important applications in different industries including textile, plastic, chemical, semiconductor and many others. This paper considers an n-job m-machine lot-streaming flow shop scheduling problem with sequence-dependent setup times under both the idling and noidling production cases. The objective is to minimize the maximum completion time or makespan. To solve this important practical problem, a novel estimation of distribution algorithm (EDA) is proposed with a job permutation based representation. In the proposed EDA, an efficient initialization scheme based on the NEH heuristic is presented to construct an initial population with a certain level of quality and diversity. An estimation of a probabilistic model is constructed to direct the algorithm search towards good solutions by taking into account both job permutation and similar blocks of jobs. A simple but effective local search is added to enhance the intensification capability. A diversity controlling mechanism is applied to maintain the diversity of the population. In addition, a speed-up method is presented to reduce the computational effort needed for the local search technique and the NEH-based heuristics. A comparative evaluation is carried out with the best performing algorithms from the literature. The results show that the proposed EDA is very effective in comparison after comprehensive computational and statistical analyses.This research is partially supported by the National Science Foundation of China (60874075, 70871065), and Science Foundation of Shandong Province in China under Grant BS2010DX005, and Postdoctoral Science Foundation of China under Grant 20100480897. Ruben Ruiz is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theoretical Advances" with reference DPI2008-03511/DPI and by the IMPIVA-Institute for the Small and Medium Valencian Enterprise, for the project OSC with references IMIDIC/2008/137, IMIDIC/2009/198 and IMIDIC/2010/175.Pan, Q.; Ruiz García, R. (2012). An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega. 40(2):166-180. https://doi.org/10.1016/j.omega.2011.05.002S16618040

Assessing the factors of green computing adoption among manufacturing employees: an analysis of the electrical and electronic sector

Recent trends and heavy uses of IT products and electronic gadgets have led to a proliferation of green computing studies because these wastes are not biodegradable. A significant amount of previous studies has been performed on green computing at the organizational level with most studies tend to focus on developed countries. The present study examined numerically the most influential factor towards the employees’ intention to adopt green computing and measure the intention level of employees in green computing adoption. The current study explored five adoption factors with five hypotheses have been established. These hypotheses were theorized from Theory of Planned Behaviour with emphasis on environmental concern. Previous studies from Malaysia context have primarily concentrated on green computing in education sector compared to manufacturing sector. Hence the study was conducted at electrical and electronic industries located at southern Malaysia. Questionnaires were purposely distributed to 250 respondents, however only 110 responses were valid that yielded response rate of 56%. Respondents are among the employees in IT and administration department that equipped with ICT application. The finding verifies the most influential factor affecting green computing adoption is environmental concern with 43.8%. All factors were proved to have positive correlation to the green computing intention. This correlation is related to the high intention level of employees in practicing green computing due to headquarters initiatives and the conditions set by the importing countries. Social norms have less impact towards behavioral intention to practice green computing that manifested by the low correlation percentage. The current study contributes to our knowledge on the green computing intention among manufacturing employees in Malaysia besides the implications of the results and future research directions. This study will help the policy makers in promoting environmental awareness among users of computing devices

On scheduling and simulation within a GT cell

In this research, detailed level scheduling within a GT cell has been investigated. For detailed level scheduling within a GT cell two classes of procedures named operation scheduling and job-group scheduling procedure have been identified. Both the procedures were investigated using simulation of randomly generated job sets;Six heuristic criteria were investigated under operation scheduling. Two of these were found to be better than SPT for savings in setup time and throughput time;A procedure to recognize setup similarity prior to scheduling has been developed using similarity measures and clustering techniques. Five rules were developed for sequencing the subgroups formed by clustering;The utility of job-group scheduling procedure as a scheduling technique for a future GT cell has been discussed. Also, the utility of the procedure to study MRP-GT interactions and to establish release times and due dates have been discussed;An efficient FORTRAN based software has been developed to simulate a GT cell and evaluate scheduling rules

Exact and Heuristic Algorithms for the Job Shop Scheduling Problem with Earliness and Tardiness Over a Common Due Date

Scheduling has turned out to be a fundamental activity for both production and service organizations. As competitive markets emerge, Just-In-Time (JIT) production has obtained more importance as a way of rapidly responding to continuously changing market forces. Due to their realistic assumptions, job shop production environments have gained much research effort among scheduling researchers. This research develops exact and heuristic methods and algorithms to solve the job shop scheduling problem when the objective is to minimize both earliness and tardiness costs over a common due date. The objective function of minimizing earliness and tardiness costs captures the essence of the JIT approach in job shops. A dynamic programming procedure is developed to solve smaller instances of the problem, and a Multi-Agent Systems approach is developed and implemented to solve the problem for larger instances since this problem is known to be NP-Hard in a strong sense. A combinational auction-based approach using a Mixed-Integer Linear Programming (MILP) model to construct and evaluate the bids is proposed. The results showed that the proposed combinational auction-based algorithm is able to find optimal solutions for problems that are balanced in processing times across machines. A price discrimination process is successfully implemented to deal with unbalanced problems. The exact and heuristic procedures developed in this research are the first steps to create a structured approach to handle this problem and as a result, a set of benchmark problems will be available to the scheduling research community