Technical Sessions A4 - G4
SESSION A4: Applied Operations Research
 Conversion Algorithms with a reward function and interrelated conversion rates
Pascal Schroeder, Robert Dochow and Günter Schmidt
We consider the non-preemptive and preemptive form of uni-directional conversion and use a reward function and interrelated conversion rates. We solve these conversion forms on-line, generalize the established algorithms UND and DIV and extent them with reward functions to derive the algorithms reward UND and reward DIV. We show that these algorithms are optimal in comparison to other on-line solutions.
 A COLUMN GENERATION ALGORITHM FOR THE TEAM ORIENTEERING PROBLEM WITH TIME WINDOWS
Racha El-Hajj, Aziz Moukrim, Bilal Chebaro and Mohamed Kobeissi
The Team Orienteering Problem with Time Windows (TOPTW) is a well-known variant of the Vehicle Routing Problem (VRP) whose aim is to maximize the total amount of profit collected from the visited customers while taking into consideration some resource limitations. In this variant, customers must be served at most once in their time windows while respecting the predefined maximum travel time limit of each vehicle. In this paper we propose a column generation based algorithm to solve the linear relaxation of TOPTW. A dynamic programming algorithm is used to solve the subproblems in order to generate additional columns. Experiments conducted on the benchmark of TOPTW show the effectiveness of our algorithm and the strengthen of our formulation since we were able to prove the optimality of several instances by finding their integer solutions at the root node while solving the linear relaxation of the model.
 RESOURCE CONSTRAINED PROJECT SCHEDULING: A BRANCH AND CUT APPROACH
Ripon Kumar Chakrabortty, Ruhul Sarker and Daryl Essam
This paper considers a deterministic resource constrained project scheduling problem (RCPSP) with an objective of makespan minimization. RCPSP is usually formulated as a mixed integer linear programming model and the model is then solved using either an exact algorithm or heuristics. However, the traditional exact algorithms are inefficient for larger activity problems. In this paper, we implemented a specialized approach Coin-Branch & Cut (CBC) solver, adapted from OPTI toolbox, which has not been applied to RCPSP earlier. To judge the performance of the algorithm, the numerical results are reported for 30, 60, 90 and 120-activity benchmark problems from the project scheduling problem library (PSPLIB). Depending on instance characteristics, the instances which are notoriously difficult were preliminary targeted to solve. Computational results are also reported to compare this algorithm with some other heuristic and exact approaches. We were able to find competitive results by using our CBC algorithm particularly for those larger activity instances.
 A Memetic algorithm for the vehicle routing problem with stochastic demands
Andres Gutierrez, Laurence Dieulle, Nacima Labadie and Nubia Velasco
This article introduces a Memetic algorithm to solve the Vehicle Routing Problem with Stochastic Demands. Computational results show that the method outperforms two of the three state-of-the-art metaheuristics and is highly competitive in terms of quality and efficiency compared to the best metaheuristic when is tested on 40 instances in the literature. Moreover the method can be easily extendable to solve other stochastic problems taking into account both problems with recourse as well as probabilistic constraints.
SESSION B4: Multi-Criteria Decision Making and Decision Analysis
 MULTI-CRITERIA ANALYSIS OF SUPPLIER SELECTION USING AHP, FUZZY-AHP, FUZZY-TOPSIS, IRP AND WEIGHTED-IRP: A COMPARATIVE STUDY
Nilesh R. Ware, Surya Prakash Singh and D. K. Banwet
The paper is an attempt to carry out multi-criteria analysis of supplier selection by applying AHP, Fuzzy-AHP, Fuzzy-TOPSIS, IRP and Weighted IRP MCDM techniques. The comparison is done on supplier selection problem to analyze the variation in the ranking results. In the paper, six broad criteria and twenty two sub-criteria are considered to test the results. The comparative study is a novel attempt where well known MCDM techniques are compared with the relatively new MCDM techniques i.e. IRP and Weighted-IRP. The comparison shows that there is no variation as far as ranking is concerned; however, there are slight variations in the ranking weights obtained. It is also proposed here that such comparison is done on large scale where other techniques such as ELCETRE, PROMETHEE, VICKOR should have been also applied. Also, the comparison is required on large data set where more number of alternatives is present to actually check the variation in ranking. Based on the results obtained in this paper, it can said that the ranking do not deviates from one technique to another.
 AN INVESTIGATION ON CRM IMPLEMENTATION FAILURE THROUGH A SYSTEM APPROACH CASE STUDY: AN IRANIAN PRIVATE TRAVEL AGENCY
Abouzar Ilkhani, Shahnaz Piroozfar and Seyed Hossein Hosseini
Nowadays, in unpredictable and complex world of business, enterprises face great challenges to meet customer’s requirements. Many of these enterprises tend to implement CRM concepts and tools to have their customers satisfied. This paper is made to present that despite CRM systems are always valuable and seem profitable, they are really costly and may fail. In order to achieve these objectives, a travel agency which had implemented CRM systems was investigated as a case study and a dynamic model for its failure was proposed through system approach. First, all different factors that could be effective were identified through a questionnaires and interviews. Later, casual loop diagrams using value tools like system dynamic was produced .At the end, using DEMATEL method which was explained in this paper, factors were prioritized and finally impressionable and effective factors were recognized.
In this paper, we aim to produce casual loop diagrams for CRM implementation failure and discuss the point that if simple factors that seem insignificant to decision makers are not taken into serious consideration, they might result in unpleasant consequences.
 ANALYSIS OF WORKSHOP LOCATION WITH LAGRANGE INTERPOLATION
Sara Haddou Amar and Abdellah Abouabdelah
The workspace location is an important strategic decision, it's a long term decision that influence the production flow and the future company development. Indeed the localization process is very difficult to master , as many qualitative and quantitative criteria should be considered in the decision of the implementation.
We propose in this paper, a multi-criteria system for workshop location analysis decision. The system is based on mathematical modeling and linguistic analysis using AHP method and Lagrange interpolation. the study is expanded to include an uncertain case and a quality index to measure the credibility of the results.
 IDENTIFY SOFTWARE QUALITY INDICATORS BASED ON FUZZY DELPHI METHOD
Shahnaz Piroozfar, Roohollah Barzi and Mohammad Ali Afshar Kazemi
Quality in software industry can be categorized in three groups: internal quality, external quality and quality in run time but to consider a software quality depends on environment in which software has been implemented. Many studies have been accomplished to define a framework for measuring software quality [1,2]. There are many models for assessing software quality such as ISO9126,ANSI Standard,McCall, Bohem, Dromey,… . Software assessment models are defined based on qualitative attributes and their relationships in various categories. These models are used to assess non-functional requirements. In most qualitative assessment models, evaluation indicators are presented in two measurable levels which called external attributes and internal attributes. This paper based on literature review, considers indicators of McCall and Dromey models. These two models focus on dynamic nature of software such as changeability. As, our research is in stock exchange sector in Iran, and this sector is a dynamic sector which needs to update software continuously based on customer requirements and continuous changes in rules, these two models selected for this purpose .First, we determine all of these two models indicators, then we used Fuzzy Delphi to choose the main criteria in McCall and Dromey.
SESSION C4: Environment & Green Industrial Engineering
 An Evolutionary Approach for Scheduling Solar-Thermal Power Generation System
Md Forhad Zaman, Dr Saber Mohammed Elsayed, A.Prof. Tapabrata Ray and A.Prof. Ruhul A. Sarker
For the scheduling of electrical power generators, it is important to search for alternatives to conventional energy sources, such as solar. In this paper, a dynamic economic dispatch model which meets the hourly load demand in a 24-hour time horizon is considered, that includes both thermal and solar sources as well as the effect of the gas emissions of a thermal plant and a realistic scenario of sun irradiations. To solve this complex, non-smooth and mixed-integer problem, an efficient evolutionary framework based on a genetic algorithm and a new heuristic is proposed. The heuristic is designed to obtain a good-quality feasible solution from an infeasible one using a priority-based local search approach. The framework is applied to a recent case study and a comparison of its results with those from other state-of-the-art techniques reveals that the proposed approach has some merits in terms of solution quality and efficiency.
 EMPIRICAL RESEARCH ON KEY INFLUENCING FACTORS OF CO2 EMISSION IN THE RUNNING PROCESS OF URBAN RESIDENTIAL BUILDINGS
Xianchun Tan, Lele Dong, Baoguang Xu, Baihe Gu and Dexue Chen
Urban residential buildings, whose CO2 emission always account for about 24% of that in China’s construction department, have become one of the key areas to control CO2 emission growth by China’s local building department. According to the energy using characteristics of urban and rural buildings, the paper firstly determines the calculation boundaries and content of CO2 emissions in the running process of urban residential buildings and then adopts LMDI emissions factors decomposition model to identify the key influencing factors of urban residential buildings. Finally, we verify the result through Granger causality test. The research results show that compared to 2000, the CO2 emissions in 2011 in the running process of urban residential buildings of the case city have increased by 121.6%. The key influencing factors of it are energy consumption per unit area, per capita living space and the urbanization rate.
 ECO-EFFICIENCY FOR SUSTAINABLE MANUFACTURING PLANNING DECISIONS WITH APPLICATIONS TO AUTO PARTS INDUSTRY
Hager M. Salama, Noha M. Galal and Aziz E. Elsayed
Although manufacturing is a vital contributor to economic development, it is frequently considered a source of negative environmental impact. It is therefore that sustainable manufacturing assessment has recently attracted the attention of researchers and practitioners to ensure that the economic, environmental and social benefits of manufacturing activities are achieved. Most of the research work on sustainable manufacturing concentrates on the product design phase. Few efforts have made benefit of sustainability assessment when making production planning decisions. In this paper eco-efficiency is applied to aid decision makers in making informed production planning and operational decisions. The approach has been applied to five different products in the automotive part production to simultaneously assess manufacturing cost and environmental impact. Life Cycle Assessment (LCA) has been performed to quantify the environmental impact. The results obtained allow for planning an eco-efficient product mix as well as for benchmarking manufacturer’s performance. On operational level, the LCA results facilitate identifying possibilities for process improvement.
 HEURISTIC APPROACH FOR THE ENVIRONMENTAL VEHICLE ROUTING PROBLEM
Jouhaina Chaouachi and Ezzeddine Fatnassi
This paper studies the distance constrained vehicle routing problem DCVRP from an environmental
aspect. We introduce in this paper a specific model while aiming to reduce the environmental effect
caused by routing of vehicles. In this work, the environmental impact is measured through the
integration of various factors such as speed, weight of the vehicles and so on. A genetic algorithm
(GA) is designed to solve the proposed problem. Preliminaries computational results suggest the
good performance of our algorithm.
SESSION D4: Design & Complex Engineering Systems
 HOLONIC CONTROL SYSTEM: REFERENCE DESIGN ARCHITECTURE FOR SOUTH AFRICAN TOOLING INDUSTRIAL CLUSTERS
Mncedisi Trinity Dewa, Andre Francois Van der Merwe and Stephen Matope
Managing the occurrence of operational disturbances during production has become a major area in sustaining global competitiveness. Some researchers and scholars have identified Holonic Control Systems (HCSs) as the paradigm appropriate for system reconfiguration and response in the face of production interruptions. However, the design and deployment of these applications can be challenging due to the existence of different proposed and tested design architecture suitable for their realization. In the article, a systematic approach is used to compare and contrast the PROSA (Product Resource Order Staff Architecture) and the ADACOR (Adaptive Holonic Control Architecture) approaches. The purpose of the comparison was for the selection of the most appropriate reference architecture for building a Holonic Control System for firms in the tool making sector in South Africa. A framework based on the organizational structure of industrial clusters in the Tool, Die and Mould-making (TDM) sector was employed as a basis for the comparison and final selection.
 RESEARCH ON THE UNCOUPLING METHOD OF MULTIDISCIPLINARY DATA FLOW IN INTEGRATED DESIGN FOR COMPLEXENGINEERING SYSTEM
Fei Xiao, Qiang Liu and Bei Jia
Decoupling is the core issue in multidisciplinary design, which is significant to improving design methods for complex engineering systems and enhancing design efficiency. Because of the basic position of the data in multi-disciplinary integrated design software, data coupling problem becomes one of the bottlenecks which obstructs deeper applications of integration software in complex engineering system design. From the perspective of an integrated software development, and taking into account of the principle of ""on - off"" and interface isolation of software design, this paper studies on the versatility and portability of data uncoupling method, and develops an interface independent data streams decoupler, which can be applied in multidisciplinary integrated design system. Integrated with multi-objective optimization framework, the paper discusses the workflow decoupling and reengineering method based on process matrix, and introduces the cluster analysis method to establish data flow decoupling model. The application in the vehicle design project proves that the extended workflow engine can deal with the multidisciplinary design problem, and can obtain the global feasible solutions of the problem, which may provides ideas for further research and applications of integrated design data flow management technology.
 DECIDING THE LEVEL OF AUTOMATION DURING THE DESIGN OF ASSEMBLY SYSTEMS: LITERATURE REVIEW OF DECISION METHODS AND A NEW APPROACH PROPOSAL
Anas Salmi, Pierre David, Eric Blanco and Joshua D. Summers
This paper reviews research in the field of automation deciding for assembly systems design. The purpose is to analyze the decision making methodologies already developed in the topic, evaluating previous efforts against practical use by manufacturers in such complex and important decision. Based on this study, a procedure is proposed to support the decision making process regarding the automation throughout the workstations of assembly systems during early conceptual design phase. Requirements for the decision methods are defined. The evaluations and analyzes of existing methods lead to a new decision approach then evaluated against the identified requirements. It is tailored to assist systems designers and decision makers in the determination of the appropriate automation level for their assembly systems.
 REQUIREMENTS INTEROPERABILITY METHOD TO SUPPORT INTEGRATED PRODUCT DEVELOPMENT
Anderson Luis Szejka, Osiris Canciglieri Junior, Eduardo Rocha Loures, Hervé Panetto and Alexis Aubry
Nowadays, more and more the complexity of product has increased. Moreover, product development must meet all costumers’ needs. This complexity has required the establishments of different patterns with additional enterprises to complement their skills. However, the definition of the different patterns with heterogeneous knowledge can share information is important to avoid the risk of misinterpretation. So, product requirements must consider all constraints during the product realization. In this way, researches have identified that there are different issues related to requirement analysis and maintenance during the product realisation. In order to cope with these issues, a conceptual approach to formally model the requirements interoperability is proposed in terms of transformations and traceability. Initially, the authors have proposed a characterisation of product to identify the requirements interoperability issues and the results were: (i) domains; (ii) product life cycle; and (iii) product requirements. Based on these characterisation, the conceptual approach used a formal logic descriptions and ontology application to transform requirements written in natural language to requirements written in formal language (mathematical language). As a result, the research presented an overview of the existing gaps in one or more requirements interoperability to cope with the requirements inconsistency problem in multiples perspectives in product development.
SESSION E4: Supply Chain Management & Logistics
 DEVELOPING A TWO-STAGED P-MEDIAN LOCATION-ALLOCATION MODEL CONSIDERING NONLINEAR ESTABLISHMENT COSTS AND PROPOSING A RECURSIVE TWO-PHASED ALGORITHM
Mehdi Seifbarghy and Taiebeh Davoodabadi
This research investigates the design of distribution network in a supply chain. A given number of production plants and distribution warehouses are located and also the best strategy for distributing products from the plants to the warehouses and from the warehouses to the customers is determined. In this paper, a new type of facility location model, which combines the aspects of the well-studied simple un-capacitated and capacitated facility location problems, is introduced. The distinctive feature is that unit production costs at the plants are considered to increase with scale of the output. We propose a two-phased simulated annealing-based heuristic in order to solve the problem. The performance of the given heuristic is assessed using a number of numerical examples.
 WAREHOUSE POOLING SPECIFICITIES: A PRELIMINARY STUDY
Mourad Makaci, Paul Reaidy, Karine Evrard Samuel, Valérie Botta Genoulaz and Thibaud Monteiro
Today, Warehouse Pooling (WP) presents a major issue for supply chains actors. However, managing such structures establishes a more complex and little known actions system. In this paper, we provide the main specificities of warehouse pooling examined from both a literature review and an exploratory study built on seven cases in France. This study is based on semi-structured interviews with 22 companies managing projects in the field of warehouse pooling. From this data, we distinguish the main characteristics of WP such as the compatibility and maturity of the partners, shared VMI (Vendor Managed Inventory) and collaborative management. Also, we identify new key performance indicators (KPIs), uncertainty sources and risks of warehouses pooling. This work helps to define WP and brings managers a better understanding of how WP can be driven. Furthermore, it allows researchers to develop new models of optimization considering the pooling context.
 FRAMEWORK FOR CLOSED LOOP SUPPLY CHAIN MODELING
Hadi Fors, Nermine Harraz and M. Hamdy Elwany
SESSION F4: Heuristics and Approximation Algorithms for Combinatorial Problems
 A fast algorithm for solving the max-min knapsack problem with two scenarios
Thekra Aldouri, Mhand Hifi and Sagvan Saleh
In this paper we propose an adaptive neighborhood search-based heuristic for solving the max-min knapsack problem with two scenarios. The proposed method consists of three complementary steps. The first step yields a feasible solution by following a greedy procedure. The second step applies an intensification procedure in the neighborhood of a current solution in order to improve its quality. The third and last step diversifies the search process by degrading the quality of the solution at hand with the aim of escaping from local optima. The proposed approach is evaluated on benchmark instances taken from the literature, where the presented results are compared to those reached by the recent methods available in the literature. The results provided show that the method is very fast and competitive since it is able to reach solutions better than those realized by the best algorithms available in the literature.
 AN STATISTICAL APPROACH FOR THE FINE-TUNING OF METAHEURISTICS: A CASE STUDY COMBINING DESIGN OF EXPERIMENTS AND RACING ALGORITHMS
Eduardo Barbosa, Edson Senne and Messias Silva
The setup of heuristics and metaheuristics, that is, the fine-tuning of its parameters, exercises a great influence in both the solution process, as well as in the quality of results of optimization problems. The search for the best fit of these algorithms is an important task and a major research challenge in the field of metaheuristics. The fine-tuning process requires a robust statistical approach, in order to aid in the process understand and also in the effective settings, as well as an efficient algorithm which can summarize the search process. This paper aims to present a study on applying Design of Experiments (DOE) techniques combined with racing algorithms in the fine-tuning of different algorithms, such as Simulated Annealing (SA) and Genetic Algorithm (GA), to solve a classical scheduling problem. It will be presented a results comparison considering the default metaheuristics and ones using the settings suggested by the fine-tuning procedure. Broadly, the fine-tuning process improves the quality of the solutions and allows for both GA and SA stay closer to optimal for different instances of the problems. Therefore, by means of this study it can be concluded that the use of DOE techniques combined with racing algorithms may be a promising and powerful tool to assist in the investigation, as well as in the fine-tuning of different algorithms.
 An Reactive Search for the Two-Edge Disjoint Survivable Network Design Problem with Relays
Adel Bouchakhchoukha, Mhand Hifi and Sagvan Saleh
In this paper, we propose a reactive search for approximately solving the two-edge disjoint surviv- able network design problem with relays. The objective of the problem is to minimize the network design cost while making sure that each commodity can be routed from a series of couples without exceeding a prefixed upper bound imposed on paths. The proposed approach is mainly based upon two complementary phases. The first phase determines and improves the quality of the solutions. The second phase reacts by considering both diversification and intensification strategies. The performance of the proposed approach is evaluated on a set of benchmark instances taken from literature. The obtained results are compared to those reached by the more recent algorithms available in the literature. It remains competitive by yielding new solutions when compared to those published in the literature.
 VECTOR EVALUATED GENETIC ALGORITHM FOR THE BI-OBJECTIVE MINIMUM SUM COLORING PROBLEM
Hend Bouziri, Jouhaina Siala and Olfa Harrabi
The sum coloring problem is a variant of the graph coloring problem. Its goal is to find a vertex coloring of a graph, using natural numbers, such that the total sum of colors assigned to vertices is minimized among all proper vertex colorings of the graph. The problem has recently received a lot of attention since it has many application domains in scheduling and distributed resource allocation.
In this paper, we propose a bi-objective formulation in which we aim to minimize the number of colors and conflicting nodes. To solve this problem, we propose an evolutionary algorithm.
Experiments are performed on instances extracted from the second DIMACS and COLOR02 challenges. Results show significant improvements on existing chromatic sum bounds.
SESSION G4: Mining and classification models for Biomedical data or image analysis
A Study on the Evaluation and Accuracy of Anatomic and Mirror Image Reconstruction Design Technique
Emad Abouel Nasr, Abdulrahman Al-Ahmari, Khaja Moiduddin, Mohammed Al Kindi and Ali Kamrani
In medical and surgery applications, the implant design is the key. Any mismatch in the implant design results in the implant failure as well as psychological stress and pain to the patient. Measuring and inspecting the geometrical implant design with the reference model is very important, to ensure the proper fitting and safety of the patient. The purpose of this study is to perform the evaluation between two geometrical design techniques- mirroring and anatomical design, commonly used in the reconstruction of the customized mandible implants. The results of the three-dimensional (3D) deviation analyses demonstrate that the Average deviation of the anatomical design model is in the range of -0.0841 to 0.1167 mm which is less compared to mirroring technique model with a range of -0.4456 to 0.4322 mm. The two dimensional (2D) geometrical surface deviation illustrates that the mirror reconstruction technique has more deviation (2.05 mm) from the reference mandible model when compared to the anatomy reconstruction technique (1.22 mm).
SKULL FAILURE-CORRECTION MODELLING METHOD BY SYMMETRY MIRRORING
Marcelo Rudek, Gustavo Campana Mendes, Osiris Canciglieri Junior and Marcos Da Silveira
This current work presents a proposal of a method for anatomical prosthesis modelling in order to generate the geometric parameters for the implants manufacturing. The concept of this proposed method is to fill the skull bone failure with the individual own skull shape by symmetric mirroring, from its non-affected opposed bone area. By using its own shape our main goal is to respect and preserve the individual morphology. A software prototype was developed as a plug-in at the Java based image processor (ImageJ) in order to generate a virtual 3D modelled anatomical prosthesis by applying all the proposed procedures. We apply the method upon a lateral skull failure as study case in order to demonstrate all the process and to discuss the evaluation of results.
ANATOMIC PROSTHESIS MODELLING BASED ON DESCRIPTORS BY CUBIC BÉZIER CURVES
Marcelo Rudek, Yohan Bonescki Gumiel, Gerson Linck Bichinho, Marcos Da Silveira and Osiris Canciglieri Junior
This paper presents a method based on image analysis to build models of the skull prosthesis as a pre-manufacturing process. The method is based on Cubic Bezier Curves as descriptors of the skull bone curvature. The method performs a symbolic representation of shape in order to define the geometric parameters to fit an arc on each Computed Tomography slice. The Bezier descriptors can be used as a template for the retrieval of similar images from medical databases whose parameters match the sampled image. The similarity is measured according to the best fitness values through ABC (Artificial Bee Colony) optimization algorithm. The slices found by similarity are retrieved from different skull images in order to build the 3D model. The 3D printing parameters can be based on images extracted from different medical images to mold a customized piece. A case study shows that the proposed method is a promising technique for 3D modelling.