Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains

Kaveh Khalili-Damghani,Peiman Ghasemi 대한산업공학회 2016 Industrial Engineeering & Management Systems Vol.15 No.2

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products’ demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multiproduct supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer’s and retailers’ decisions are optimized through a coordination mechanism making lasting relationship.

Solving a New Multi-Period Multi-Objective Multi-Product Aggregate Production Planning Problem Using Fuzzy Goal Programming

Khalili-Damghani, Kaveh,Shahrokh, Ayda Korean Institute of Industrial Engineers 2014 Industrial Engineeering & Management Systems Vol.13 No.4

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.

A Hybrid Approach Based on Multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) to Evaluate Efficiency of Customer Services in Bank Branches

Kaveh Khalili-Damghani,Mohammad Taghavi-Fard,Kiaras Karbaschi 대한산업공학회 2015 Industrial Engineeering & Management Systems Vol.14 No.4

A hybrid procedure based on multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) is proposed to evaluate the relative efficiency of customer services in bank branches. First, a three-stage process including sub-processes such as customer expectations, customer satisfaction, and customer loyalty, is defined to model the banking customer services. Then, fulfillment of customer expectations, customer loyalty level, and the customer satisfaction degree are measured and quantified through a multi-dimensional questionnaire based on customers’ perceptions analysis and MUSA method, respectively. The customer services scores and the other criteria such as mean of employee evaluation score, operation costs, assets, deposits, loans, number of accounts are considered in network three-stage DEA model. The proposed NDEA model is formed based on multipliers perspective, outputoriented, and constant return to scale assumptions. The proposed NDEA model quantifies and assesses the total efficiency of main process and assigns the efficiency to customer expectations, customer satisfactions, and customer loyalties sub-processes in bank branches. The whole procedure is applied on 30 bank branches in IRAN. The proposed approach can be used in other organizations such as airports, airline agencies, urban transportation systems, railway organizations, chain stores, chain restaurants, public libraries, and entertainment centers.

Solving a New Multi-Period Multi-Objective Multi-Product Aggregate Production Planning Problem Using Fuzzy Goal Programming

Kaveh Khalili-Damghani,Ayda Shahrokh 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.4

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of endproduct, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the reimplementation of the model for future development and case studies.

A Hybrid Approach Based on Multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) to Evaluate Efficiency of Customer Services in Bank Branches

Khalili-Damghani, Kaveh,Taghavi-Fard, Mohammad,Karbaschi, Kiaras Korean Institute of Industrial Engineers 2015 Industrial Engineeering & Management Systems Vol.14 No.4

A hybrid procedure based on multi-Criteria Satisfaction Analysis (MUSA) and a Network Data Envelopment Analysis (NDEA) is proposed to evaluate the relative efficiency of customer services in bank branches. First, a three-stage process including sub-processes such as customer expectations, customer satisfaction, and customer loyalty, is defined to model the banking customer services. Then, fulfillment of customer expectations, customer loyalty level, and the customer satisfaction degree are measured and quantified through a multi-dimensional questionnaire based on customers' perceptions analysis and MUSA method, respectively. The customer services scores and the other criteria such as mean of employee evaluation score, operation costs, assets, deposits, loans, number of accounts are considered in network three-stage DEA model. The proposed NDEA model is formed based on multipliers perspective, output-oriented, and constant return to scale assumptions. The proposed NDEA model quantifies and assesses the total efficiency of main process and assigns the efficiency to customer expectations, customer satisfactions, and customer loyalties sub-processes in bank branches. The whole procedure is applied on 30 bank branches in IRAN. The proposed approach can be used in other organizations such as airports, airline agencies, urban transportation systems, railway organizations, chain stores, chain restaurants, public libraries, and entertainment centers.

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

Khalili-Damghani, Kaveh,Ghasemi, Peiman Korean Institute of Industrial Engineers 2016 Industrial Engineeering & Management Systems Vol.15 No.2

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

A New Stochastic Time-Cost-Quality Trade-Off Project Scheduling Problem Considering Multiple-Execution Modes, Preemption, and Generalized Precedence Relations

Reza-Pour, Farahnaz,Khalili-Damghani, Kaveh Korean Institute of Industrial Engineers 2017 Industrial Engineeering & Management Systems Vol.16 No.3

Project managers always try to make the best decisions in order to complete their projects in the shortest period of time, with the least amount of costs, and with the highest degree of quality. Therefore, the process of decision-making is conducted in a triangle of time, costs, and quality. This triangle is a crucial part of management process throughout the execution of the project. However, in all problems, some unpredictable situations may be faced. In such situations, some or all parameters of the problem are expressed by uncertain variables. In this paper, a stochastic time-cost-quality trade off project scheduling problem (STCQTP) considering multiple-execution modes, preemption, and generalized precedence relations is developed. In order to solve the STCQTP, a hybrid solution approach based on Stochastic Chance Constraint Programming (SCCP) and Goal Programming (GP) is proposed. SCCP and GP are used to handle the uncertain nature and multiple-objectives of STCQTP, respectively. Numerical example is solved in order to illustrate the applicability of proposed model and solution approach.

A New Stochastic Time-Cost-Quality Trade-Off Project Scheduling Problem Considering Multiple-Execution Modes, Preemption, and Generalized Precedence Relations

Farahnaz Reza-Pour,Kaveh Khalili-Damghani 대한산업공학회 2017 Industrial Engineeering & Management Systems Vol.16 No.3

Project managers always try to make the best decisions in order to complete their projects in the shortest period of time, with the least amount of costs, and with the highest degree of quality. Therefore, the process of decision-making is conducted in a triangle of time, costs, and quality. This triangle is a crucial part of management process throughout the execution of the project. However, in all problems, some unpredictable situations may be faced. In such situations, some or all parameters of the problem are expressed by uncertain variables. In this paper, a stochastic time-costquality trade off project scheduling problem (STCQTP) considering multiple-execution modes, preemption, and generalized precedence relations is developed. In order to solve the STCQTP, a hybrid solution approach based on Stochastic Chance Constraint Programming (SCCP) and Goal Programming (GP) is proposed. SCCP and GP are used to handle the uncertain nature and multiple-objectives of STCQTP, respectively. Numerical example is solved in order to illustrate the applicability of proposed model and solution approach.