International Journal of Industrial Engineering: Theory, Applications and Practice
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Dynamic Matching of Uncertain Demand with Uncertain Supply for Bike Sharing Systems
No full textIn Operations Management, most production and inventory models incorporate either demand uncertainty or supply uncertainty as input. When both uncertainties are involved, they are treated separately with an intermediary inventory stock and they are not directly linked in analysis. In this paper, we address a new problem of matching uncertain demand with uncertain supply directly. The problem arises in bike sharing systems that feature uneven and dynamic flow of bikes across bike stations. Besides periodical rebalancing, dynamic rebalancing of bikes is crucial to upholding service quality but is a costly transportation operation. We present an analysis of the solution characteristics and show that it is frequent to have multiple optimal solutions which give rise to dispersed transfers of bikes. As dynamic rebalancing is aimed at resolving the imbalance problem selectively at critical points, we construct a mathematical programming model to evaluate the utility of each transfer to facilitate prioritizing candidate transfers. By analyzing the numerical results of the mathematical programming and deep learning models, we conclude that rule-based heuristic methods are suitable for dynamic rebalancing of bike sharing systems
Multi-Trip Open Vehicle Routing Problem with Time Windows: A case study
No full textIn this paper, we introduce a practical variation of the standard vehicle routing problem (VRP). The problem is a combination of the multi-trip, open and VRP with time windows. A practical application of the introduced problem is to provide service for the university professors. In the studied problem, a set of professors have to teach at a university located in another city. The goal is planning and scheduling services for professors in order to minimize the total transportation cost with a set of side constraints including the maximum travel time for each passenger. We provide two mathematical models namely, node-based and scenario-based formulations. In addition, we present a heuristic method to produce feasible scenarios for the scenario-based model. Computational results clearly indicate the effectiveness of the models by solving real size instances
A New Approach for Sensitivity Analysis in Network Flow Problems
No full textThis paper proposes a new approach to study the sensitivity analysis in the network ow problems, in particular, the minimum spanning tree and shortest path problems. In a sensitivity analysis, one looks for the amount of changes in the edges' weights, number of edges or number of vertices such that the optimal solution, i.e. the minimum spanning tree or shortest path does not change. We introduce a novel approach for this purpose, and develop associated mathematics. We discusstwo illustrative examples to show the applicability of the proposed approach
A PROFIT-MAXIMIZING MODEL FOR INTEGRATED LOT-SIZING AND SCHEDULING PROBLEM WITH MULTI-ITEM SUPPLIER SELECTION AND DEMAND PACKAGES
No full textThis research proposes a mathematical model in which the procurement and production lot-sizing are integrated with scheduling. In this model, the procurement lot-sizing comprises supplier selection and multiple transportation modes. This profit-maximizing model is developed with demand choice flexibility using two arrangements: with and without demand packages. The results represent that the objective function value of the model with demand packages is less than the model without packages while the computational time of the model with packages is greater than the other one. The impact of demand’s correlation on results is investigated through solving the problem with two correlation levels. Results show that the number of setups, total costs, and the number of incomplete packages are influenced by the demand correlation. Besides, the objective function value of the problem with positive demand correlation is higher. Results also certify the impact of discount schemes on productions, purchases, costs, and revenues
BI-OBJECTIVE AGE-BASED PRODUCTION-DISTRIBUTION PLANNING FOR PERISHABLE PRODUCTS
No full textSupply chain management of perishable products especially fresh food is different from other types of products because of extraordinary amount of wastage during inventory holding in facilities and transportation process. With considering production and distribution planning simultaneously waste costs will probably be reduced. Although, a lot of integrated production-distribution planning models were presented, an integrated model with considering fresh food specifications in objective functions and constraints is still needed. In this paper, we present a multi-objective age-based integrated production-distribution planning model. Our focus is on perishable products particularly fresh food and fresh products. The proposed model is of integer linear programming type that aims to minimize simultaneously sum of the production, inventory holding, wastage costs and sum of the freshness related costs and transportation costs. The balanced box method is applied to find non-dominated solutions for the proposed bi-objective model. Numerical experiments are conducted to evaluate the applicability and validity of the proposed model. Our results show that fresh products related specifications must be taken into account in the objective and constraints simultaneousl
A Meta-Heuristic Solution Approach for the Destruction of Moving Targets through Air Operations
No full textMoving Target Traveling Salesman Problem is the problem of destruction of targets moving at certain angles and speeds by a constant velocity pursuer. The problem is applied in many areas, mainly production, defense and surveillance systems. Military operations constitute the most strategic branch of these areas of application. In this study, a new solution algorithm is proposed based on simulated annealing for destruction of moving targets through air operations at minimum time. Six different heuristic algorithms, three of which were used for the first time, were developed for the initial solution of the algorithm, and the best two constructors were used as the initial solution in simulated annealing algorithm. Effectiveness of the proposed algorithms were tested on 20 different scenarios and it was found that the SA-MDH method (minimum distance - simulated annealing algorithm) gives better results than the SA-MTH method (minimum time - simulated annealing algorithm)
STRUCTURED REGULARIZATION MODELING FOR VIRTUAL METROLOGY IN SEMICONDUCTOR MANUFACTURING PROCESSES
No full textVirtual metrology (VM) has been developed to economically perform wafer-to-wafer control, and has been used to estimate actual measurements from process data collected via sensors attached to corresponding equipment. Sensor data contains a large number of highly correlated and grouped features. Despite great potential of structured regularization models for addressing the group structure in sensor data, little effort has been made to examine their performance in terms of VM modeling. The main objective of this study is to propose use of structured regularization models for VM modeling and compare them with unstructured regularization models in terms of predictive accuracy, feature-selection accuracy, and stability. The effectiveness of unstructured regularization models was demonstrated through experiments with synthetic data as well as real data obtained during semiconductor manufacturing processes. Results of these experiments demonstrate that feature-selection accuracy and stability of structured regularization models were superior to those of corresponding unstructured regularization models
METAHEURISTIC ALGORITHMS FOR FLEXIBLE FLOW SHOP SCHEDULING PROBLEM WITH UNRELATED PARALLEL MACHINES
No full textFlexible flow shop scheduling problems (FFS) with multiple unrelated machines are common manufacturing environments in many industries, such as the semiconductor, steel, ceramic tile and lead frame industries. This work proposes an improved mathematical model to solve the problem with minimum makespan objective. Since the research problem is shown to be NP-hard, two versions of the PSO, two versions of the GA, and a Hybrid PSO-GA (HPG) algorithm, are applied to solve the problem, approximately. The proposed meta-heuristic algorithms are tested on some test problems, inspired by Carlier and Néron’s benchmark problems. Computational results show that all the proposed algorithms can efficiently and effectively minimize the makespan, and the HPG is the most effective
A FUZZY-BASED DECISION SUPPORT MODEL FOR EFFECTIVENESS EVALUATION – A CASE STUDY OF EXAMINATION OF BULLDOZERS
No full textEffectiveness evaluation is one of basic components in engineering asset management. It is overall concept and represents measurement of quality of service level for selected engineering system. Effectiveness contains series of partial indicators related to time in operation and time for maintenance activities, as well as to functional properties of the system. This article describes analysis and structuring of partial indicators, as well as development of model for their synthesis to the level of effectiveness. Indicators have hybrid character (measured values and experts judgments), and the fuzzy inference model is suggested for their processing and integration into the effectiveness. This approach provided possibility for evaluation of a technical system in sense of decision making about remaining capabilities and optimization of life cycle costs. To demonstrate the opportunities of developed model for effectiveness evaluation, case study related to bulldozers is presented. Bulldozers are machines operating at difficult conditions, usually under pressure to achieve required performance with low stoppages and minimal costs during overall operational life. Case study included two approaches. First one is based on data collected by experts’ judgments, while the other one is based on measurement and statistical processing of dat
DESIGNING A CLOSED-LOOP SUPPLY CHAIN NETWORK AND PROVIDING A MULTI-OBJECTIVE MATHEMATICAL MODEL TO SELECT A THIRD-PARTY LOGISTICS COMPANY AND SUPPLIER SIMULTANEOUSLY
No full textIn this study, a closed-loop supply chain network is designed. The solution for the applied model is determined in two phases. First, third-party logistics (3PLs) and external suppliers are selected by using grey theory. The outputs are the weight of 3PLs and suppliers. Second, a multi-objective mixed-integer linear programming model (MOMILP) is proposed. Through this model, 3PLs and suppliers are selected, and the optimal amount of returns to 3PLs and parts purchased from suppliers are determined. The proposed model considers the simultaneous selection of 3PLs and suppliers. The contribution of this study is a novel configuration of the multi-stage, multi-period, multi-product closed-loop supply chain network and 3PL and supplier selection by using grey theory, wherein a MOMILP is developed to implement the network and partner allocation. The supplier hub is utilized in the proposed network, which has rarely been accomplished in the previous literature. Finally, a numerical example is provided