Revised Interative Goal Programming Using Sparsity Technique on Microcumputer

Gen, Mitsuo,Ida, Kenichi,Lee, Sang M. 한국경영과학회 1985 韓國經營科學會誌 Vol.10 No.1

Recently, multiple criteria decision making has been well established as a practical approach to seek a satisfactory solution to a decision making problem. Goal programming is one of the most powerful MCDM tools with satisfying operational assumptions that reflect the actual decision making process in real-world situations. In this paper we propose an efficient method implemented on a microcomputer for solving linear goal programming problems. It is an iterative revised goal simplex method using the sparsity technique. We design an interactive software package for microcomputers based on this method. From some computational experiences, we can state that the revised iterative goal simplex method using the sparsity technique is the most efficient one for microcomputers for solving goal programming problems.

Hotel Management Model

Mitsuo Gen,Seren Ozmehmet Tasan,Kayoko Hirano 대한산업공학회 2008 대한산업공학회 춘계학술대회논문집 Vol.2008 No.5

In recent years, companies in the hospitality and tourism industry have been facing the competitiveness under the pressure of globalization. In such an environment, especially human resource management plays an important role helping the hotel to maintain or improve its place in the service environment. In human resource management, resource allocation, where allocation of the resources to the tasks has to be done in an effective way, is one of the central problems faced in hospitality and tourism industry. Traditionally, in academic literature, most of the researchers simplified the resource allocation problem and ignored some real-world issues such as operational precedence constraints among the tasks and skill requirements for the resources. In the past decade, to solve hotel management problems, several solution approaches, due to the problem complexity mostly heuristics and meta-heuristics, have been proposed. Among these solution approaches, evolutionary algorithms, which are proven to be efficient and robust, have been used in a variety of fields including hotel management area to find an optimal solution for the problem. The purpose of this tutorial is to present the applications of evolutionary algorithms in hotel management systems. The intent of the tutorial is to enable the researchers and practitioners in the conference to promote a better understanding of human resource allocation model with operational precedence constraints and skill requirements in real-world and evolutionary algorithm applications to solve this model.

Multiobjective Genetic Algorithm for Scheduling Problems in Manufacturing Systems

Mitsuo Gen,Lin Lin 대한산업공학회 2012 Industrial Engineeering & Management Systems Vol.11 No.4

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic populationbased metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

Soil gamasid mites: their diversity and availability as bioindicators

Gen Takaku,Minako Takagi,Ayaka Fukuda,Mitsuo Sogabe 한국응용곤충학회 2008 한국응용곤충학회 학술대회논문집 Vol.2008 No.10

Gamasida (Acari, Parasitiformes) is one the most diverse group in mites, and they inhabit in various environments, for example soil, tree canopy, tree trunk, leaves, animal, inter-tidal zone. About 10,000 species have been described in the world, half of them are predatory mites in soil and litter, and they prey on nematodes, small insects and mites. Although many predatory gamasid mites have been recorded from soil and litter in Japan, difference of diversity and difference of species composition of gamasid mites in different soil environments have not surveyed and discussed yet. In the present study, we surveyed soil gamasid mites in urban environment in Sapporo City, Hokkaido, Japan, and compared with gamasid mites in secondary forests (mixed forest, deciduous broad-leaved forest) in and near Sapporo. Our study focused on the following points: 1) difference of diversity in each environment; 2) characteristic taxa in each envrironment; and 3) availability of some taxa as bioindicator to evaluate environment. Number of species and index of diversity were higher in the fauna of secondary forests. Diversity of the families Parasitidae and Laelapidae were higher in urban environment fauna, while diversity of Parholaspidae and Veigaiidae were higher in the forest one. In the forest, mites of the family Zerconidae appeared exclusively, whereas one species of the family Parholaspidae and Parasitidae were dominant in urban mite fauna. Family Zerconidae and some species of Parholaspidae and Parasitidae may be available as bioindicator to evaluate soil environment.

Evolutionary Network Design

Mitsuo Gen,Lin Lin 대한산업공학회 2008 대한산업공학회 추계학술대회논문집 Vol.2008 No.11

Network design is one of the most important and most frequently encountered classes of optimization problems. It is a combinatory field in combinatorial optimization and graph theory. When considering a bicriteria network design (bND) problem with the two conflicting objectives of minimizing cost and maximizing flow. Network design problems where even one flow measure be maximized, are often NP-hard problems. But, in real-life applications, it is often the case that the network to be built is required to optimize multi-criteria simultaneously. Thus the calculation of the multi-criteria network design problems is a difficult task. In this state-of-the-art survey paper, we propose a new multiobjective hybrid genetic algorithm (mo-hGA) hybridized with Fuzzy Logic Control (FLC) and Local Search (LS). Numerical experiments based on the mo-hGA method for designing multiple objective network models show the effectiveness and the efficiency of our approach by comparing with the recent researches.

Hotel Management Model

Mitsuo Gen,Seren Ozmehmet Tasan,Kayoko Hirano 한국경영과학회 2008 한국경영과학회 학술대회논문집 Vol.2008 No.5

In recent years, companies in the hospitality and tourism industry have been facing the competitiveness under the pressure of globalization. In such an environment, especially human resource management plays an important role helping the hotel to maintain or improve its place in the service environment. In human resource management, resource allocation, where allocation of the resources to the tasks has to be done in an effective way, is one of the central problems faced in hospitality and tourism industry. Traditionally, in academic literature, most of the researchers simplified the resource allocation problem and ignored some real-world issues such as operational precedence constraints among the tasks and skill requirements for the resources. In the past decade, to solve hotel management problems, several solution approaches, due to the problem complexity mostly heuristics and meta-heuristics, have been proposed. Among these solution approaches, evolutionary algorithms, which are proven to be efficient and robust, have been used in a variety of fields including hotel management area to find an optimal solution for the problem. The purpose of this tutorial is to present the applications of evolutionary algorithms in hotel management systems. The intent of the tutorial is to enable the researchers and practitioners in the conference to promote a better understanding of human resource allocation model with operational precedence constraints and skill requirements in real-world and evolutionary algorithm applications to solve this model.

A Brief Review of Penalty Methods in Genetic Algorithms for Optimization

Mitsuo Gen,Runwei Cheng 대한산업공학회 1996 대한산업공학회 춘계학술대회논문집 Vol.1996 No.4

Survey of Evolutionary Algorithms in Advanced Planning and Scheduling

Mitsuo Gen,Wenqiang Zhang,Lin Lin 대한산업공학회 2009 대한산업공학회지 Vol.35 No.1

Recent advances in hybrid evolutionary algorithms for multiobjective manufacturing scheduling

Gen, Mitsuo,Zhang, Wenqiang,Lin, Lin,Yun, YoungSu Elsevier 2017 COMPUTERS & INDUSTRIAL ENGINEERING Vol.112 No.-

<P><B>Abstract</B></P> <P>In real manufacturing systems there are many combinatorial optimization problems (COP) imposing on more complex issues with multiple objectives. However it is very difficult for solving the intractable COP problems by the traditional approaches because of NP-hard problems. For developing effective and efficient algorithms that are in a sense “good,” <I>i.e.</I>, whose computational time is small as within 3min, we have to consider three issues: quality of solution, computational time and effectiveness of the nondominated solutions for multiobjective optimization problem (MOP).</P> <P>In this paper, we focus on recent <I>hybrid evolutionary algorithms</I> (HEA) to solve a variety of single or multiobjective scheduling problems in manufacturing systems to get a best solution with a smaller computational time. Firstly we summarize <I>multiobjective hybrid genetic algorithm</I> (Mo-HGA) and <I>hybrid sampling strategy-based multiobjective evolutionary algorithm</I> (HSS-MoEA) and then propose <I>HSS-MoEA combining with differential evolution</I> (HSS-MoEA-DE). We also demonstrate those hybrid evolutionary algorithms to <I>bicriteria automatic guided vehicle</I> (B-AGV) dispatching problem, <I>robot-based assembly line balancing problem</I> (R-ALB), <I>bicriteria flowshop scheduling problem</I> (B-FSP), multiobjective scheduling problem in <I>thin-film transistor-liquid crystal display</I> (TFT-LCD) module assembly and <I>bicriteria process planning and scheduling</I> (B-PPS) problem. Also we demonstrate their effectiveness of the proposed hybrid evolutionary algorithms by several empirical examples.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Various real manufacturing systems are considered. </LI> <LI> Multiobjective scheduling problems in manufacturing systems are considered. </LI> <LI> Recent hybrid evolutionary algorithms are proposed. </LI> </UL> </P>

A Brief Review of Penalty Methods in Genetic Algorithms for Optimization

Gen, Mitsuo,Cheng, Runwei 한국경영과학회 1996 한국경영과학회 학술대회논문집 Vol.- No.1

Penalty technique perhaps is the most common technique used in the genetic algorithms for constrained optimization problems. In recent years, several techniques have been proposed in the area of evolutionary computation. However, there is no general guideline on designing penalty function and constructing an efficient penalty function is quite problem-dependent. The purpose of the paper is to give a tutorial survey of recent works on penalty techniques used in genetic algorithms and to give a better classification on existing works, which may be helpful for revealing the intrinsic relationship among them and for providing some hints for further studies on penalty techniques.