International Journal of Industrial Engineering: Theory, Applications and Practice
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DISCOVERING DISASTER EVENTS FROM SOCIAL MEDIA STREAMS
No full textNatural and man-made disasters can both cause severe loss of lives and economic damages. Examples include earthquakes, floods, and road crashes. Nevertheless, to rapidly and accurately identify the latest status of a disaster event is undoubtedly one of the most difficult tasks for agencies in crisis management. In this work, we thus propose to monitor online data streams in social media for detecting and tracking real world events. Unlike conventional media, social media is advantageous because of its immediateness, huge data scale, and worldwide availability. Nevertheless, the messages generated by netizens could be incomplete, subjective, or even error prone. Only with an appropriately designated scheme, invaluable clues embedded in huge amounts of online messages can be discovered when carefully exploiting the information over content, temporal, and social dimensions. Specifically, we collect data from multiple social networks, conduct real-time analysis, and present interactive visualization. Experimental studies show that the proposed scheme is demonstrated to be feasible for agencies in practice
A bi-objective inventory model to minimize cost and stock out time under backorder shortages and screening
No full textAlthough minimizing costs is the main objective in inventory models, meeting customer's needs is another basic goal of many companies. Especially in the case shortages are allowed, the waiting time a customer spends to receive his/her backlogged shortage is an important factor that affects maintaining with the company. As defining an accurate shortage cost which includes cost of losing customers and cost of damaging brand image is not possible for many companies, the above two objectives are considered in this paper to develop a bi-objective inventory model, in which the total cost of a retailer and his customers’ stock out times are minimized. In this model, the order size, the maximum backordering quantity, and the number of inspectors are defined as the decision variables, where a 100% screening process with the rate higher than the demand rate is used to screen out the items. After screening, the non-conforming items are stored in the warehouse, where they will be exchanged with new items when a new order is arrived at the end of the cycle. The bi-objective optimization problem is solved using the non-dominated sorting genetic algorithm (NSGA-II). As there is no benchmark available in the literature, another multi-objective optimization algorithm called the multi-objective particle swarm optimization (MOPSO) is employed to validate the result and to evaluate the performance of NSGA-II. Computational results of solving some randomly generated numerical examples are in favor of MOPSO
AN EFFICIENT LOSS FUNCTION APPROACH TO OPTIMIZE CORRELATED MULTI-RESPONSES
No full textIn quality engineering, engineering intuition is often ineffective and inconclusive for interpreting the behaviors of quality characteristics and their possible effects on process loss. Loss functions can be utilized in process design and optimization by aligning losses in a way which minimizes expected losses, even when responses are correlated and losses are the result of co-movements of those responses, i.e., synergy or antagonism of loss. Most of the current literature on multidimensional quality does not provide enough information about the effects of responses moving simultaneously in the same/opposite direction on process loss. To fill this gap, this manuscript focuses on co-movement effects and provides an efficient approach based on multivariate upside-down normal loss function. The procedure and its advantages are illustrated by an example
A NOVEL METHODOLOGY FOR TIME PLANNING OF RESOURCE-CONSTRAINED SOFTWARE PROJECTS WITH HESITANT FUZZY DURATIONS: A CASE STUDY
No full textTime planning of software projects is a complex process for almost all companies. Uncertainties about effort required may cause underestimation or overestimation. Thus, enterprises may encounter an unrealistic schedule and choosing the appropriate planning method becomes crucial. This paper presents a novel integrated decision support methodology for time planning of resource constrained software projects. For this aim, after identifying the effective criteria by the help of expert judgments from the Turkish Information Technology industry and literature review, we find their priorities by Hesitant Fuzzy Pairwise Comparison and calculate estimated effort for the projects. Then, we use the priorities of criteria and estimated durations of the projects in a mathematical programming model proposed to find starting and finishing (delivery) time of the projects. Furthermore, we apply the methodology for solving the project time planning problem of a Turkish software company. It is seen that the proposed method provides efficient schedules
EXTENSION OF MCDM METHOD FOR SUPPLIER SELECTION PROBLEM WITH INTERVAL NUMBERS BASED ON OBJECTIVE WEIGHTING
No full textSelecting the most appropriate supplier is considered to be the main primary concern in supply chain because the producers spend most of their time on supplying the raw materials and spare parts. Moreover a lion’s share of cost is allocated to buying goods and services. During the past years there were many methods to evaluate and select the suppliers but traditional models of supplier selection were based on quantitative data and they paid less attention to qualitative and imprecise data. In this paper a compromise solution of interval VIKOR is presented to develop a method for evaluating and selecting the appropriate suppliers. On the other hand, the objective weights based on Shannon entropy which is fitted with imprecise data are used to eliminate the mental error caused by subjective judgment. At the end a numerical example is presented to demonstrate the application of proposed method in selecting the suppliers
STREET WASHING TRUCK ROUTING WITH INTERMEDIATE REFILL FACILITIES
No full textThe capacitated arc routing problem (CARP) is to determine a set of tours that traverse a set of required arcs with capacitated limitation on vehicles. There are many practical applications for variants of the CARP, including street washing and snow removal. The aim of this paper is to discuss the street washing truck routing problem with intermediate refill points (SWRPIR), a variant of the capacitated arc routing problem. Routes for street washing trucks are normally planned in advance and must be designed to take into account the vehicle capacity. Street washing vehicles could refill water at intermediate refill points without going back to the depot to save time. Due to that SWRPIR is an NP-hard problem, we proposed an ant colony optimization (ACO) algorithm to solve the problem. The ACO is tested with benchmark instances and real world cases. The results indicate that our ACO is competitive in benchmark instances with compared algorithms and can reduce the total distance for the washing vehicles for real world cases
MODELLING AND DECISION SUPPORT SYSTEM FOR INTELLIGENT MANUFACTURING: AN EMPIRICAL STUDY FOR FEEDFORWARD-FEEDBACK LEARNING-BASED RUN-TO-RUN CONTROLLER FOR SEMICONDUCTOR DRY-ETCHING PROCESS
No full textThis study aims to address the formation of various decision models based on modeling, analytics, and optimization techniques for intelligent manufacturing and smart production. Indeed, smart manufacturing deals with flexible decisions for addressing the dynamic, competitive, and global supply chains and production networks by employing advanced information technology, intelligent computerized control, digital decision technologies, and high levels of adaptability. While research in the broad area of smart manufacturing and its challenges in decision making encompasses a wide range of topics and methodologies, this study provides a good snapshot of current quantitative modeling approaches, issues, and trends. The validity of the proposed framework is estimated with a number of illustrations. This study concludes with discussion of future research directions
TWO-DIMENSIONAL LEASE CONTRACT WITH PREVENTIVE MAINTENANCE USING BIVARIATE WEIBULL
No full textThis paper develops a two-dimensional lease contract for repairable products. During the contract period, all maintenance actions are carried out by the lessor. There are two customer types considered – the one whose lease contract end because a usage limit and the other type whose lease contract cease because the time limit has reached first. The proposed model uses a two-dimensional approach, and model failures using a bivariate Weibull distribution. When the age or usage of equipment reaches a specified limit, an imperfect preventive maintenance is conducted and each PM will reduce the failure rate level of the equipment. Furthermore, if the equipment fails, a minimal repair corrective maintenance is performed. As an illustration, a numerical example is presented to show the optimal preventive maintenance that minimizes lessor’s maintenance cost, and the expected number of breakdowns during leased contract period. This proposed model will be compared with a recent relevant approach through numerical computation
TARGET SIZE, POSITION AND MOVEMENT DIRECTION EFFECTS ON THE DRAG TASK PERFORMANCE OF A GAZE CONTROL DEVICE
No full textAn eye mouse is an alternative input device which can perform most of the tasks that a conventional mouse can, it is usually used by disabled people. Although the usability of an eye mouse has not been investigated exhaustively, a few studies have focused on the drag tasks of an eye mouse. This study evaluated the performance of drag tasks by an eye mouse according to target size, position, and movement direction. Twenty-seven participants were recruited to perform drag tasks. The results indicated that the diagonal movement worked better than horizontal movement, which worked better than vertical movement. The upper horizontal movement worked better than the lower one. Also, the eye mouse worked better with large targets than with small or medium ones. The results of this study should help in designing interfaces or applications for an eye mouse
FAMILY SPLITTING ALGORITHM FOR A SINGLE MACHINE TOTAL TARDINESS SCHEDULING PROBLEM WITH JOB FAMILY SETUP TIMES
No full textWe study a single machine scheduling problem with sequence-dependent setup time to minimize total tardiness. The jobs are grouped by family. Processing jobs in the same family does not need set up; otherwise there is a fixed amount of setup time between families. A family of jobs can be split. We present a heuristic procedure to solve this NP hard problem. The procedure generates a temporary schedule to estimate the impact of setup time on the performance, and then determineswhether or not a family splitting is necessary at the cost of additional setup time. The heuristic procedure is applied on a large set of test problems, and its performance is compared to that of the Apparent Tardiness Cost with Setup (ATCS) procedure, which is known for effectively minimizing the total tardiness of a schedule with setup time. Test results show that the proposed algorithm significantly reduces the tardiness