International Journal of Industrial Engineering: Theory, Applications and Practice
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Lower Bounds For Hierarchical Chinese Postman Problem
Get PDFArc routing problems aim at finding a least cost traversal on a network with or without additional constraints. The Hierarchical Chinese Postman Problem (HCPP) is an arc routing problem. HCPP is NP-hard and several heuristics have been developed to solve this problem. The Chinese Postman Problem (CPP) tour solution is a known lower bound for the HCPP. This paper presents a heuristic that will prescribe improved lower bounds for the HCPP when compared to the CPP solutions. Better lower bounds aid exact search methods, such as branch-and-bound, to find an optimal solution in a shorter run time. It can also be used to determine the quality of a heuristic solution. Several problem instances were generated to evaluate the proposed heuristic. Experimental results indicate that our lower bounds are better than the CPP solution for all the sample problems chosen
Design of An Artificial Neural Network for Assembly Sequence Planning System
Get PDFThe problem of assembly sequence generation is complex and has proven to be difficult to solve. Various method have been used in attempting to solve the problem, including mathematical modeling and search techniques. This paper presents an investigation for analyzing assembly sequences of assembly systems with a proposed neural network predictor. The proposed neural network has three layers with recurrent structure. A fast learning algorithm Backpropagation (BP) algorithm is employed for updating the weight parameters of the proposed network
Heuristic Genetic Algorithm for Workforce Scheduling with Minimum Total Worker-Location Changeover
Get PDFThis paper presents a heuristic genetic algorithm (GA) to find daily work assignments without hazard exposure. Its objective is twofold: (1) to determine a minimum number of workers for a given set of worker locations, and (2) to determine safety work assignments with a minimum total worker-location changeover. Firstly, a hybrid procedure to determine a lower bound and the minimum number of workers is applied to generate an initial population. Then, the GA with heuristic crossover and mutation is utilized to search for a safety work assignment solution. The swap and multi-start algorithms are also employed to improve the GA solution. The heuristic GA is able to solve both balanced and unbalanced work assignment problems. Comparing with an optimization approach, the GA can generate the safety work assignments with the minimum total worker-location changeover in much shorter computation tim
Strategic Paradigms for Manufacturing Management (Spmm): Key Elements and Conceptual Model
Get PDFThis paper proposes a new concept in Manufacturing Management: Strategic Paradigm for Manufacturing Management (SPMM). This new concept aims to deal with the 20th century manufacturing management paradigms in a comparative and integrated way. To accomplish this goal four key elements are identified: drivers (market conditions that require SPMM implementation); performance objectives (representing the operation’s strategic objectives that each SPMM gives priority to); principles (the SPMM fundamentals) and enablers (the tools, technologies and methods of each SPMM). The main contributions of this paper are: i) the presentation of a conceptual model that relates the SPMM to operation’s strategic objectives; and, ii) the possibility of allowing comparisons and analyses of the manufacturing paradigms, facilitating the study and practical application of these paradigms. The proposed model deals with strategic questions in the Production/Operations Management context in a very pragmatic way. To illustrate the proposed model five case examples are presented.
MULTI-OBJECTIVE SIMULATION OPTIMIZATION: A CASE STUDY IN HEALTHCARE MANAGEMENT
No full textThis study presents an approach to solve multi-response simulation optimization problems. This approach integrates a simulation model with a genetic algorithm heuristic and a goal programming model. This method was modified to perform the search considering the mean and the variance of the responses. This way, the selection process of the genetic algorithm is performed stochastically, and not deterministically like most of the approaches reported in the literature. The methodology was tested using a simulation model of a cancer treatment facility created by the authors. The multi-objective optimization heuristic was successfully used to improve the performance of the model relative to four different system objectives. Empirical results show that the methodology is capable of generating an important part of the Pareto optimal 'frontier, mostly concentrated in the center portion, where practical solutions are generally located
PLANT LOCATION SELECTION USING FUZZY DIGRAPH AND MATRIX METHODS
No full textIn the present work, a methodology based on fuzzy digraph and matrix methods is developed for evaluation of alternative plant locations. Attributes which characterize plant location selection are identified and are called the 'plant location attributes'. Consideration of these attributes and their interrelations are rudiment in evaluation. Tbis is modeled in terms of a 'plant location attributes digraph'. The digraph is represented by a one-to-one matrix and the 'permanent function' of this matrix leads to the development of a characteristic expression, which is useful in comparing the alternative plant locations. 'Plant location selection index' is obtained from the 'pennanent function' of the matrix by substituting numerical values of the attributes and their interrelations. A step by step procedure for evaluation of 'plant location selection index' is suggested. The methodology is illustrated by means of an example
PREFACE FOR THE SPECIAL ISSUE ON LOGISTICS AND MARITIME SYSTEMS
No full textThe first International Conference on Logistics and Maritime Systems (LOGMS) was held in Busan, Korea, from September 15 to 17, 2010. The conference was launched by integrating the International Conference on Intelligent Logistics System (IILS) and the International Symposium on Maritime Logistics and Supply Chain Management (MLOG). With the increase in economic activities and the globalization of international trade, logistics has become a key factor in global companies. As mentioned by Professor Kap Hwan Kim, the chair of organizing committee, the worldwide economic situation has become more interconnected, uncertain, and dynamic; the traditional approaches to logistics and maritime management are no longer sufficient. The conference provided an opportunity for the researchers to discuss and exchange information, knowledge, ideas, and technologies regarding the development of logistics and maritime systems.About 200 participants from 17 countries actively participated in the conference. There were 31 technical sessions with 112 presentations along with 4 keynote speeches. Various topics were discussed in the technical sessions, such as seaport and transportation, maritime, shipping, supply chain management, inventory and production, simulation, business process management for logistics, which are closely related to the logistics and maritime system.Thirty two papers from the 112 papers were invited by the Program Committee for this special issue. Finally, 18 papers were accepted after a thorough review process. Several papers were related to empty container repositioning. Long et al. considered the planning for maritime empty container repositioning using a case study that involved 49 ports and 44 services. Yun et al. addressed inland container transportation in which the containers are transported by trucks and trains with time windows. Some papers studied the operations of a container terminal, such as Sung et al., Choi et al., and Daduna. Other papers were related to inventory management, logistics process management, and the maintenance system; thus, this issue covers a broad spectrum on logistics and maritime systems.For the success of this issue, I would like to express our deep appreciation to the reviewers who provided thorough reviews to the papers. Moreover, I would like to thank Professor Mital and Professor Pennathur for their support in bringing out this issue. I am quite sure that this special issue will provide important references for logistics and maritime studies. Professor ILKYEONG MOON, Guest EditorDepartment of Industrial Engineering, Seoul National UniversitySeoul, KOREAEmail: [email protected]
A TWO-STAGE ROBUST METHOD FOR FLEXIBLE INTEGRATED MASTER SURGICAL SCHEDULING AND CASE-MIX PLANNING
No full textThis paper investigates the integrated master surgical scheduling and case-mix planning problem with the objective of a weighted sum of minimizing the costs of overtime and idle time, increasing surgeons' preferences, and reducing uncovered demands. Considering the uncertainty in surgery demands, a robust optimization model is proposed. A two-stage method is designed for creating and updating this scheduling with respect to downstream resources. The first stage allocates the time blocks to each surgeon to determine the mix of surgery types assigned to each block. In the second stage, having the weekly waiting list of patients, the schedule is updated on the weekly horizon to cope with demand fluctuations and to maximize the use of operating rooms capacity. The proposed method is validated using actual data from a teaching hospital in Iran. The results of the proposed models significantly outperformed the actual plan of a hospital, which indicated the efficiency of the designed models. Comparing the deterministic and robust models shows that robust models lead to better results in over 70% of the test instances
A MULTI-CRITERIA DECISION-MAKING APPROACH FOR GREENOVATIVE SUPPLIER SELECTION
No full textIn today’s rapidly changing business environment, green and innovative (greenovative) activities have become indispensable elements of sustainable supply network management. Realization of this fact obliges firms to consider greenovative as well as traditional criteria in determining their supplier. This study provides a new greenovative systematic approach to supplier selection for small and medium-sized enterprises. Fuzzy multi-criteria decision-making (FMCDM)-based techniques were used to determine the most appropriate supplier with the proposed model. To show the usability of the model, an application was carried out on an automotive supply company. Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) approaches were used to calculate the weights of the supplier selection criteria. After determining criteria weights, different multi-criteria decision-making (MCDM) techniques that are often encountered in the literature were used to identify the best supplier
DISTRIBUTED FLOW SHOP SCHEDULING PROBLEM WITH LEARNING EFFECT, SETUPS, NON-IDENTICAL FACTORIES, AND ELIGIBILITY CONSTRAINTS
No full textIn the flow shop scheduling, the route of each job is the same, and the order of the jobs on the machines is determined. In the distributed flow shop scheduling (DFSS) problem, on the other hand, the assignment of jobs to factories is carried out in addition to the determination of the order of the jobs. Therefore, the DFSS problem is both an assignment and a sequencing problem. This study considers machine factory-dependent setup times, non-identical factories, position-based learning effects on processing times and setup times, and factory eligibility constraints for the DFSS problem. The study is the first to consider all these real-life features encountered in the DFSS problem. The addressed problem is defined considering the scheduling problem of Enterprise Resource Planning (ERP) projects. A mathematical model is proposed for the solution of the problem. Since the problem is NP-hard, a multi-start iterative tabu search (ITS) algorithm is proposed to solve large-scale problems. An encoding schema, decoding algorithm, and multi-start strategy are proposed to solve the problem with the ITS algorithm. The parameters of the proposed algorithm are determined by the Taguchi experimental design method. The success of the proposed multi-start ITS algorithm is demonstrated by comparing it with the state-of-the-art genetic algorithm (GA), simulated annealing (SA) algorithm, and tabu search (TS) algorithm through test problems and a real-world application. Statistical analysis is performed to determine the performance of the proposed heuristic. As a result, the proposed heuristic algorithm is found to be more successful than other algorithms in the literature