Publishing type：Research paper (scientific journal)   Publisher：EDP Sciences  

The covering tour problem (CTP) is defined on a graph, where there exist two types of vertices. One is called <italic>visited vertex</italic>, which <italic>can</italic> be visited. The other is called <italic>covered vertex</italic>, which <italic>must</italic> be covered but cannot be visited. Each visited vertex covers a subset of covered vertices, and the costs of edges between visited vertices are given. The objective of the CTP is to obtain a minimum cost tour on a subset of visited vertices while covering all covered vertices. In this paper, we deal with the large-scale CTPs, which are composed of tens of thousands of vertices; in the previous studies, the scales of the instances in the experiments are at most a few hundred vertices. We propose a heuristic algorithm using local search techniques for the large-scale CTP. With computational experiments, we show that our algorithm outperforms the existing methods.

DOI： 10.1051/ro/2017090

researchmap

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.tre.2017.09.004

Web of Science

researchmap

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Japanese Operations Management and Strategy Association  

Research in the field of scheduling has been undergoing a shift in recent years from a focus on nurse scheduling to that on service industry scheduling at hotels and restaurants. Reducing employment costs and figuring out how to put non-regular employments in place to cope with fluctuating demand are critical issues in this sector, particularly when it comes to the scheduling problem to the service industry that depends on human service providers. To cope with these challenges, this paper proposes a shift scheduling model that effectively takes into consideration non-regular employments specializing in food and beverage service in hotel restaurants. It also considers the use of two types of the non-regular employments who are called monthly staff and one-time staff with different working arrangements.

DOI： 10.20586/joms.6.1_17

researchmap

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/SMC.2015.346

Web of Science

researchmap

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.dam.2014.01.012

Web of Science

researchmap

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE Computer Society  

DOI： 10.1109/CoASE.2014.6899457

Scopus

researchmap

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.compeleceng.2012.12.020

Web of Science

researchmap

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Society for Industrial and Applied Mathematics Publications  

DOI： 10.1137/1.9781611972931.1

Scopus

researchmap

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1299/jamdsm.7.644

Web of Science

researchmap

Publishing type：Research paper (international conference proceedings)  

DOI： 10.20586/joms.5.1_74

researchmap

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/CEC.2012.6253012

Web of Science

researchmap

Publishing type：Research paper (international conference proceedings)  

researchmap

Language：English   Publishing type：Research paper (international conference proceedings)  

DOI： 10.1109/IEEM.2011.6117891

Web of Science

researchmap

Publishing type：Research paper (international conference proceedings)  

researchmap

Language：English   Publisher：Biomedical Fuzzy Systems Association  

We examine a technique for solving the scheduling problem in the flexible flow shop, where the processing time is uncertain. The conventional scheduling method for the flexible flow shop is usually based on afirst-in-flrst-out rule at each stage. However, there is no guarantee that a good solution can be obtained by this method, especially because of the uncertain processing time. In the present study, we attempt to develop a scheduling method that provides a robust schedule against uncertainty in the processing time. In the present paper, we consider a procedure by which to generate robust schedules depending on the degree of uncertainly.

DOI： 10.24466/ijbschs.15.1_45

researchmap

Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Mechanical Engineers  

DOI： 10.1299/kikaic.76.3220

researchmap

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Industrial Management Association  

This paper discusses a version of the vehicle routing problem with stochastic demand (VRPSD). In this problem, a customer's demand is characterized by a known probability distribution and the customer's actual demand is only revealed when the vehicle reaches the customer location. In such a problem, two approaches are proposed. The objective of the first approach is to find a route sequence that minimizes the expected travel cost. This approach has good performance stochastically; however, when it is applied an upper bound on the travel cost cannot be guaranteed. The second approach is a robust approach implemented through chance-constrained programming. The objective is to find a route sequence that is robust with respect to uncertain demands and, at the same time, minimize the travel cost. When the probability that the vehicle's route is executed as planned is high, the route is said to be robust. In chance-constrained programming, the maximum allowable probability of route failure can be specified by the planner. The chance-constrained approach may have a higher travel cost than the first approach; however, it can guarantee a boundary for worst case performance. In this paper, we employ the chance-constrained approach as a robust method. We formulate VRPSD as a set-covering problem and solve the problem using column generation. We propose an efficient method for designing the route sequences that enable the maximum allowable probability of route failure to be specified.

DOI： 10.11221/jima.60.289

CiNii Books

researchmap

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1504/IJAMS.2010.033566

Scopus

researchmap

Language：English   Publishing type：Research paper (scientific journal)  

researchmap

Publishing type：Research paper (international conference proceedings)  

researchmap

Event date： 2008.9

Language：Japanese  

researchmap

Event date： 2006.9

Language：Japanese  

researchmap

Event date： 2005

Language：Japanese  

We examine the technique for solving the scheduling problem in the flexible flow shop where processing time is uncertain. The conventional scheduling method for flexible flowshop is usually based on first out first in rule on each stage. However, there is no guarantee that a good solution can be obtained by this method, especially for the uncertain processing time. Then, in this study, we consider to express the distribution of uncertain processing time with a normal distribution. Then, we aim to develop the scheduling method which provides a robust solution to the change of the degree of uncertainty.

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap

researchmap