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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Industrial Engineering and Management Systems
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Journal DOI :
Korean Institute of Industrial Engineers
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Volume & Issues
Volume 10, Issue 4 - Dec 2011
Volume 10, Issue 3 - Sep 2011
Volume 10, Issue 2 - Jun 2011
Volume 10, Issue 1 - Mar 2011
Selecting the target year
Batch Scheduling Problem with Multiple Due-dates Constraints
Mohri, Shintaro ; Masuda, Teruo ; Ishii, Hiroaki ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 1~6
DOI : 10.7232/iems.2011.10.1.001
This paper describes the issue of batch scheduling.In food production, the lead-time from produc-tion to sale should be decreased becausefreshness of the product is important. Products are shipped at diverse times depending on a demand of sellers, because the types of sellers has become diversified such as super-markets, convenience stores and etc. production of quantity demanded must be completed by time to ship it then. The authors consider a problem with due-dates constraints and construct the algorithm to find the opti-mal schedule that satisfy the due-dates constraint, batch size constraint, inventory time constraint and mini-mize total flow time.
A Shaking Optimization Algorithm for Solving Job Shop Scheduling Problem
Abdelhafiez, Ehab A. ; Alturki, Fahd A. ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 7~14
DOI : 10.7232/iems.2011.10.1.007
In solving the Job Shop Scheduling Problem, the best solution rarely is completely random; it follows one or more rules (heuristics). The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search, which belong to the Evolutionary Computations Algorithms (ECs), are not efficient enough in solving this problem as they neglect all conventional heuristics and hence they need to be hybridized with different heuristics. In this paper a new algorithm titled "Shaking Optimization Algorithm" is proposed that follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. The results show that the proposed algorithm outperforms the GA, PSO, SA, and TS algorithms, while being a good competitor to some other hybridized techniques in solving a selected number of benchmark Job Shop Scheduling problems.
Heuristic Algorithms for Parallel Machine Scheduling Problems with Dividable Jobs
Tsai, Chi-Yang ; Chen, You-Ren ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 15~23
DOI : 10.7232/iems.2011.10.1.015
This research considers scheduling problems with jobs which can be divided into sub-jobs and do not required to be processed immediately following one another. Heuristic algorithms considering how to divide jobs are proposed in an attempt to find near-optimal solutions within reasonable run time. The algorithms contain two phases which are executed recursively. Phase 1 of the algorithm determines how jobs should be divided while phase 2 solves the scheduling problem given the sub-jobs established in phase 1. Simulated annealing and genetic algorithms are applied for the two phases and four heuristic algorithms are established. Numerical experiment is conducted to determine the best parameter values for the heuristic algorithms. Examples with different sizes and levels of complexity are generated. Performance of the proposed algorithms is evaluated. It is shown that the proposed algorithms are able to efficiently and effectively solve the considered problems.
A Hybrid Genetic Algorithm for the Location-Routing Problem with Simultaneous Pickup and Delivery
Karaoglan, Ismail ; Altiparmak, Fulya ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 24~33
DOI : 10.7232/iems.2011.10.1.024
In this paper, we consider the Location-Routing Problem with simultaneous pickup and delivery (LRPSPD) which is a general case of the location-routing problem. The LRPSPD is defined as finding locations of the depots and designing vehicle routes in such a way that pickup and delivery demands of each customer must be performed with same vehicle and the overall cost is minimized. Since the LRPSPD is an NP-hard problem, we propose a hybrid heuristic approach based on genetic algorithms (GA) and simulated annealing (SA) to solve the problem. To evaluate the performance of the proposed approach, we conduct an experimental study and compare its results with those obtained by a branch-and-cut algorithm on a set of instances derived from the literature. Computational results indicate that the proposed hybrid algorithm is able to find optimal or very good quality solutions in a reasonable computation time.
Limiting the Number of Open Projects to Shorten the NPD Schedule
Wang, Miao-Ling ; Yang, Chun-I ; Chang, Sheng-Hung ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 34~42
DOI : 10.7232/iems.2011.10.1.034
Many companies open multiple projects simultaneously due to market trends, which results in a crowding out effect because of limited resources. R&D engineers become overloaded and scheduling of product development is delayed resulting in timing misses and lost sales leads. The company in this case study (Company A), often opens up many projects simultaneously in order to respond to market needs quickly. The engineers are overloaded and, of course, the schedule is delayed. In order to identify problems, Company A began using Dr. Goldratt's Thinking Processes (TP) during new product development (NPD). When the analysis phase of TP was completed, Company A's core problem was identified as "the quantity of kick-off projects." Consequently, new rules and conditions and procedures were proposed for the opening, suspending, stopping, and closing of projects. Finally, the "Future Reality Tree" ensured that the proposed rules, conditions and procedures were set up as an available solution approved for practical application by executives. After a one-year trial run, the results showed that the Project Duration Rate was reduced by 53%, the Project Closed Rate was increased by 140% and the Project on Time Rate was increased from 10% to 68%. The above results give significant evidence of the benefits of the proposed methodology.
Establishment of "A-PPNS", A Navigation System for Regenerating the Software Development Business
Sakai, Hirotake ; Waji, Yoshihiro ; Nakamura, Mari ; Amasaka, Kakuro ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 43~53
DOI : 10.7232/iems.2011.10.1.043
Currently, knowledge within the field of software development is largely implicit and is not formally disseminated and shared. This means that there is little improvement and regeneration of processes, and knowledge gained from previous projects is not necessarily applied to new ones. In order to turn this situation around it is necessary to take an organized approach to sharing job-related information. For this study, the authors constructed "Amalab-Project Planning Navigation System, or A-PPNS", a system for organizing accumulated knowledge related to the field of software development. More specifically, A-PPNS is a business process monitoring system and consists of the following four elements: (i) Optimized estimate support subsystem, (ii) Schedule monitoring system, (iii) QCD optimization diagnostic system, and (iv) Strategic technology accumulation system. The effectiveness of this system has been demonstrated and verified at Company A, a system integration company.
A Case Study of Human Resource Allocation for Effective Hotel Management
Murakami, Kayoko ; Tasan, Seren Ozmehmet ; Gen, Mitsuo ; Oyabu, Takashi ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 54~64
DOI : 10.7232/iems.2011.10.1.054
The purpose of this study is to optimally allocate the human resources to tasks while minimizing the total daily human resource costs and smoothing the human resource usage. The human resource allocation problem (hRAP) under consideration contains two kinds of special constraints, i.e. operational precedence and skill constraints in addition to the ordinary constraints. To deal with the multiple objectives and the special constraints, first we designed this hRAP as a network problem and then proposed a Pareto multistage decisionbased genetic algorithm (P-mdGA). During the evolutionary process of P-mdGA, a Pareto evaluation procedure called generalized Pareto-based scale-independent fitness function approach is used to evaluate the solutions. Additionally, in order to improve the performance of P-mdGA, we use fuzzy logic controller for fine-tuning of genetic parameters. Finally, in order to demonstrate the applicability and to evaluate the performance of the proposed approach, P-mdGA is applied to solve a case study in a hotel, where the managers usually need helpful automatic support for effectively allocating hotel staff to hotel tasks.
Rule Induction Considering Implication Relations Between Conclusions
Inuiguchi, Masahiro ; Inoue, Masanori ; Kusunoki, Yoshifumi ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 65~73
DOI : 10.7232/iems.2011.10.1.065
In rough set literatures, methods for inducing minimal rules from a given decision table have been proposed. When the decision attribute is ordinal, inducing rules about upward and downward unions of decision classes is advantageous in the simplicity of obtained rules. However, because of independent applications of the rule induction method, inclusion relations among upward/downward unions in conclusion parts are not inherited to the condition parts of obtained rules. This non-inheritance may debase the quality of obtained rules. To ensure that inclusion relations among conclusions are inherited to conditions, we propose two rule induction approaches. The performances of the proposed approaches considering the inclusion relations between conclusions are examined by numerical experiments.
Heuristic Approach for Lot Sizing and Scheduling Problem with State Dependent Setup Time
Han, Jung-Hee ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 74~83
DOI : 10.7232/iems.2011.10.1.074
In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.
Barrier Option Pricing with Model Averaging Methods under Local Volatility Models
Kim, Nam-Hyoung ; Jung, Kyu-Hwan ; Lee, Jae-Wook ; Han, Gyu-Sik ;
Industrial Engineering and Management Systems, volume 10, issue 1, 2011, Pages 84~94
DOI : 10.7232/iems.2011.10.1.084
In this paper, we propose a method to provide the distribution of option price under local volatility model when market-provided implied volatility data are given. The local volatility model is one of the most widely used smile-consistent models. In local volatility model, the volatility is a deterministic function of the random stock price. Before estimating local volatility surface (LVS), we need to estimate implied volatility surfaces (IVS) from market data. To do this we use local polynomial smoothing method. Then we apply the Dupire formula to estimate the resulting LVS. However, the result is dependent on the bandwidth of kernel function employed in local polynomial smoothing method and to solve this problem, the proposed method in this paper makes use of model averaging approach by means of bandwidth priors, and then produces a robust local volatility surface estimation with a confidence interval. After constructing LVS, we price barrier option with the LVS estimation through Monte Carlo simulation. To show the merits of our proposed method, we have conducted experiments on simulated and market data which are relevant to KOSPI200 call equity linked warrants (ELWs.) We could show by these experiments that the results of the proposed method are quite reasonable and acceptable when compared to the previous works.