Weighted tardiness minimization for unrelated machines with sequence-dependent and resource-constrained setups

Motivated by the need of quick job (re-)scheduling, we examine an elaborate scheduling environment under the objective of total weighted tardiness minimization. The examined problem variant moves well beyond existing literature, as it considers unrelated machines, sequence-dependent and machine-dependent setup times and a renewable resource constraint on the number of simultaneous setups. For this variant, we provide a relaxed MILP to calculate lower bounds, thus estimating a worst-case optimality gap. As a fast exact approach appears not plausible for instances of practical importance, we extend known (meta-)heuristics to deal with the problem at hand, coupling them with a Constraint Programming (CP) component - vital to guarantee the non-violation of the problem's constraints - which optimally allocates resources with respect to tardiness minimization. The validity and versatility of employing different (meta-)heuristics exploiting a relaxed MILP as a quality measure is revealed by our extensive experimental study, which shows that the methods deployed have complementary strengths depending on the instance parameters. Since the problem description has been obtained from a textile manufacturer where jobs of diverse size arrive continuously under tight deadlines, we also discuss the practical impact of our approach in terms of both tardiness decrease and broader managerial insights

Common due date early

Ankara : The Department of Industrial Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.Thesis (Master's) -- Bilkent University, 2013.Includes bibliographical references leaves 91-96.This study considers a scheduling problem with position-dependent deteriorating jobs and a maintenance activity in a single machine. Even in the absence of maintenance activity and deterioration problem is NP-hard. A solution comprises the following: (i) positions of jobs, (ii) the position of the maintenance activity, (iii) starting time of the first job in the schedule. After the maintenance activity, machine will revert to its initial condition and deterioration will start anew. The objective is to minimize the total weighted earliness and tardiness costs. Jobs scheduled before (after) the due-date are penalized according to their earliness (tardiness) value. Polynomial (O(n log n)) time solutions are provided for some special cases. No polynomial solution exists for instances with tight due-dates. We propose a mixed integer programming model and efficient algorithms for the cases where mathematical formulation is not efficient in terms of computational time requirements. Computational results show that the proposed algorithms perform well in terms of both solution quality and computation time.Şirvan, FatmaM.S

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems

Variant-oriented Planning Models for Parts/Products Grouping, Sequencing and Operations

This research aims at developing novel methods for utilizing the commonality between part/product variants to make modern manufacturing systems more flexible, adaptable, and agile for dealing with less volume per variant and minimizing total changes in the setup between variants. Four models are developed for use in four important domains of manufacturing systems: production sequencing, product family formation, production flow, and products operations sequences retrieval. In all these domains, capitalizing on commonality between the part/product variants has a pivotal role. For production sequencing; a new policy based on setup similarity between product variants is proposed and its results are compared with a developed mathematical model in a permutation flow shop. The results show the proposed algorithm is capable of finding solutions in less than 0.02 seconds with an average error of 1.2%. For product family formation; a novel operation flow based similarity coefficient is developed for variants having networked structures and integrated with two other similarity coefficients, operation and volume similarity, to provide a more comprehensive similarity coefficient. Grouping variants based on the proposed integrated similarity coefficient improves changeover time and utilization of the system. A sequencing method, as a secondary application of this approach, is also developed. For production flow; a new mixed integer programing (MIP) model is developed to assign operations of a family of product variants to candidate machines and also to select the best place for each machine among the candidate locations. The final sequence of performing operations for each variant having networked structures is also determined. The objective is to minimize the total backtracking distance leading to an improvement in total throughput of the system (7.79% in the case study of three engine blocks). For operations sequences retrieval; two mathematical models and an algorithm are developed to construct a master operation sequence from the information of the existing variants belonging to a family of parts/products. This master operation sequence is used to develop the operation sequences for new variants which are sufficiently similar to existing variants. Using the proposed algorithm decreases time of developing the operations sequences of new variants to the seconds

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques

The Writing of Abstracts and SRAs by EFL Students : Analysis of Productions and Assessment of SFL Genre Pedagogy

Scientific writing is a very complex albeit crucial activity for researchers who need to share findings and become a part of, or maintain, a position as members of a wide international discourse community. Since most scientific communication happens in English, the task of writing in this foreign language for researchers in Argentinian universities is a challenge for both researchers themselves and teachers of English who need to facilitate the writing path for students. With increasing evidence of its usefulness, Genre Pedagogy has been shown to greatly improve EFL (English as a Foreign Language) writing. In this research, the Sydney School Genre Pedagogy (SSGP) approach as offered by the Systemic Functional Linguistics (SFL) perspective is applied to the teaching of writing, with a twofold aim. A linguistic objective is pursued in analyzing student-produced abstracts and Scientific Research Articles (SRAs), with a special focus on interpersonal meanings and rhetorical components in student-produced scientific discourse. Second, this investigation assesses the effectiveness of SFL Genre Pedagogy in the teaching of one of the most important scientific genres used for the communication of findings, i.e. the SRA

Multi-Agent Modeling for Integrated Process Planning and Scheduling

Multi-agent systems have been used for modelling various problems in the social, biological and technical domain. When comes to technical systems, especially manufacturing systems, agents are most often applied in optimization and scheduling problems. Traditionally, scheduling is done after creation of process plans. In this paper, agent methodology is used for integration of these two functions. The proposed multi-agent architecture provides simultaneous performance of process planning and scheduling and it consists of four intelligent agents: part and job agents, machine agent, and optimization agent. Verification and feasibility of a proposed approach is conducted using agent based simulation in AnyLogic software