فهرست مطالب

Supply and Operations Management - Volume:3 Issue: 3, 2016
  • Volume:3 Issue: 3, 2016
  • تاریخ انتشار: 1395/08/20
  • تعداد عناوین: 7
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  • Luca Dacierno *, Antonio Placido, Mariisa Botte, Mariano Gallo, Bruno Montella Pages 1351-1372
    In this paper, we propose a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordinary conditions as rapidly as possible. In this context, the use of rail simulation is vital: for each intervention strategy it provides the evaluation of interactions and performance analysis prior to actually implementing the corrective action. However, in most cases, simulation tasks are deterministic and fail to allow for the stochastic distribution of train performance and delays. Hence, the strategies adopted might not be robust enough to ensure effectiveness of the intervention. We therefore propose an off-line procedure for disruption management based on a microscopic and stochastic rail simulation which considers both service operation and travel demand. An application in the case of a real metro line in Naples (Italy) shows the benefits of the proposed approach in terms of service quality.
    Keywords: Sensitivity Analysis, Public Transport Management, Rail System, Travel Demand Estimation, Quality of Service
  • Mohammad Mirabi *, Nasibeh Shokri, Ahmad Sadeghieh Pages 1373-1390
    This paper considers the multi-depot vehicle routing problem with time window in which each vehicle starts from a depot and there is no need to return to its primary depot after serving customers. The mathematical model which is developed by new approach aims to minimizing the transportation cost including the travelled distance, the latest and the earliest arrival time penalties. Furthermore, in order to reduce the problem searching space, a novel GA clustering method is developed. Finally, Experiments are run on number problems of varying depots and time window, and customer sizes. The method is compared to two other clustering techniques, fuzzy C means (FCM) and K-means algorithm. Experimental results show the robustness and effectiveness of the proposed algorithm.
    Keywords: Vehicle Routing problem, Multi-Depot, Flexible End Depot, Genetic Algorithm, Clustering
  • Denis Pinha*, Rashpal Ahluwalia, Pedro Senna Pages 1391-1412
    This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.
    Keywords: Resource Constrained Project Scheduling, Mathematical Formulation, Discrete Event Simulation, Decision Support System
  • Masoud Rabbani *, Safoura Famil Alamdar, Parisa Famil Alamdar Pages 1413-1428
    In this study, a two-objective mixed-integer linear programming model (MILP) for multi-product re-entrant flow shop scheduling problem has been designed. As a result, two objectives are considered. One of them is maximization of the production rate and the other is the minimization of processing time. The system has m stations and can process several products in a moment. The re-entrant flow shop scheduling problem is well known as NP-hard problem and its complexity has been discussed by several researchers. Given that NSGA-II algorithm is one of the strongest and most applicable algorithm in solving multi-objective optimization problems, it is used to solve this problem. To increase algorithm performance, Taguchi technique is used to design experiments for algorithm’s parameters. Numerical experiments are proposed to show the efficiency and effectiveness of the model. Finally, the results of NSGA-II are compared with SPEA2 algorithm (Strength Pareto Evolutionary Algorithm 2). The experimental results show that the proposed algorithm performs significantly better than the SPEA2.
    Keywords: Re, entrant Manufacturing System, Non-dominated Sorting Genetic Algorithm (NSGA-II), Taguchi Parameter Setting
  • Ali Akbar Hasani * Pages 1429-1441
    In this paper, a comprehensive model is proposed to design a network for multi-period, multi-echelon, and multi-product inventory controlled the supply chain. Various marketing strategies and guerrilla marketing approaches are considered in the design process under the static competition condition. The goal of the proposed model is to efficiently respond to the customers’ demands in the presence of the pre-existing competitors and the price inelasticity of demands. The proposed optimization model considers multiple objectives that incorporate both market share and total profit of the considered supply chain network, simultaneously. To tackle the proposed multi-objective mixed-integer nonlinear programming model, an efficient hybrid meta-heuristic algorithm is developed that incorporates a Taguchi-based non-dominated sorting genetic algorithm-II and a particle swarm optimization. A variable neighborhood decomposition search is applied to enhance a local search process of the proposed hybrid solution algorithm. Computational results illustrate that the proposed model and solution algorithm are notably efficient in dealing with the competitive pressure by adopting the proper marketing strategies.
    Keywords: Supply Chain Management, Marketing Strategies, Hybrid Metaheuristic, Non-dominated sorting genetic algorithm-II, Particle swarm optimization, Variable neighborhood decomposition search
  • Hamid Tikani, Mahboobeh Honarvar *, Yahia Zare Mehrjerdi Pages 1442-1459
    In this paper, we study the problem of integrated capacitated hub location problem and seat inventory control considering concept and techniques of revenue management. We consider an airline company maximizes its revenue by utilizing the best network topology and providing proper booking limits for all itineraries and fare classes. The transportation system arises in the form of a star/star network and includes both hub-stop and non-stop flights. This problem is formulated as a two-stage stochastic integer program with mixed-integer recourse. We solve various instances carried out from the Turkish network data set. Due to the NP-hardness of the problem, we propose a hybrid optimization method, consisting of an evolutionary algorithm based on genetic algorithm and exact solution. The quality of the solutions found by the proposed meta-heuristic is compared with the original version of GA and the mathematical programming model. The results obtained by the proposed model imply that integrating hub location and seat inventory control problem would help to increase the total revenue of airline companies. Also, in the case of serving non-stop flights, the model can provide more profit by employing less number of hubs.
    Keywords: Perishable products, P-hub Median, Seat Allocation, Evolutionary Algorithms, Fare alass Segmentation, Network Revenue Management
  • Seyed Ali Ziaee Azimi *, Mohammad Saidi, Mehrabad Pages 1460-1479
    The present research is classified as an applied one employing a descriptive survey design to describe the status quo of the factors affecting customers’ satisfaction with the E-service centers of Iran’s police, known as 10 police centers. The research population involves all the costumers of the 10 police centers, among which 420 individuals were chosen through simple random sampling technique. Furthermore, 45 10 police service centers were selected with probability proportional to size. After Determining the validity and reliability of the researcher-made questionnaire, it has been used to collect the required data. Then, a conceptual model was developed using the theoretical framework and background literature. After that, SPSS software was used to examine and make an analysis of the research hypothesises. The findings indicate that all the identified indices to the customers’ satisfaction with the 10 police e- service centers (including trust and confidence, staff performance, system facility, environmental facility, basic amenity, providing sufficient notification, time and cost, easy access to the office) have an effect on the customers’ satisfaction. In the end, some practical suggestions were made for an improvement in the satisfaction level of the customers to the 10 police e- service centers.
    Keywords: 10 +police, Measuring the Customer Satisfaction, Improvement in Quality of the Services