Necati Aras | Bogazici University (original) (raw)

Papers by Necati Aras

We focus on the order picking operation carried out in one of the major warehouses of a retailer ... more We focus on the order picking operation carried out in one of the major warehouses of a retailer to satisfy the orders placed by the stores of the same retailer. We investigate the simultaneous solution of the storage assignment problem and picker routing problem referred to as JSAPRP that involves both assigning items to storage locations and deciding on the routes of the pickers for item collection. The performance measure of interest is the minimization of the total traveling distance of the pickers. We develop a mathematical model which can only solve small instances of the JSAPRP. Therefore, we also devise a heuristic method based on adaptive large neighborhood search. Computational results obtained on numerous experiments reveal that the quality of the solutions produced by this heuristic is quite good.

European Journal of Operational Research

IISE Transactions

Abstract The Influence Maximization Problem has been widely studied in recent years, due to rich ... more Abstract The Influence Maximization Problem has been widely studied in recent years, due to rich application areas including marketing. It involves finding k nodes to trigger a spread such that the expected number of influenced nodes is maximized. The problem we address in this study is an extension of the reverse influence maximization problem, i.e., misinformation minimization problem where two players make decisions sequentially in the form of a Stackelberg game. The first player aims to minimize the spread of misinformation whereas the second player aims its maximization. Two algorithms, one greedy heuristic and one matheuristic, are proposed for the first player’s problem. In both of them, the second player’s problem is approximated by Sample Average Approximation, a well-known method for solving two-stage stochastic programming problems, that is augmented with a state-of-the-art algorithm developed for the influence maximization problem.

International Transactions in Operational Research

Future Generation Computer Systems

Abstract The popularity of traditional network services and web content is succeeded by the recen... more Abstract The popularity of traditional network services and web content is succeeded by the recent trend in customized services proliferated by the smart devices and gadgets. Fall-risk assessment, augmented reality, ECG (electrocardiography) monitoring, virtual reality-based gaming and similar services are driven through data generated by multi-modal sensors embedded in the end-user equipment. These services may possess varying characteristics and requirements represented with performance metrics and Quality of Service (QoS) parameters. Even though the small form-factor end-user gadgets are getting powerful in terms of resource capacity, they are still incapable of executing complex routines, and thus these tasks should be offloaded to a remote machine. Service-Centric Networks (SCN) focus on delivering customized services to the users in a location-independent fashion. This is in parallel with previous vision put forward by the Information-Centric Networks (ICN) and Content Delivery Networks (CDN), which aim to enhance the end-user experience. The novel set of services for complementing the daily activities of the end-users mostly depicts a latency-intolerant attribute which ultimately calls for a full-fledged resource allocation scheme. Within this context, both computation and networking resources should be allocated optimally, and task assignments should be handled precisely for following the requirements specified by the Service Level Agreements (SLAs). This paper initially presents and discusses problem definitions that should be addressed by the service-centric multi-tier computing architecture that is composed of edge, metro, and cloud servers. In order to achieve this objective, an SLA-aware optimal resource allocation and task assignment model for service-oriented networks is proposed. This optimization model is based on a nonlinear delay formulation for accommodating service-centric network scenarios under various conditions. It is then reshaped as a mixed-integer linear model through piecewise linear approximation. Additionally, a heuristic implementation is presented to address the time and space complexities of the problem for which the aforementioned optimization models remain ineffective. Performance evaluation results show that the proposed solutions are able to find a good allocation of resources while taking the requirements of the services into account.

Journal of Remanufacturing

Closed-loop supply chains involve forward flows of products from production facilities to custome... more Closed-loop supply chains involve forward flows of products from production facilities to customer zones as well as reverse flows from customer zones back to remanufacturing facilities. We present an integrated modeling framework for configuring a distribution system with reverse flows so as to minimize the total cost of satisfying customer demand and remanufacturing the returned items that are recoverable. Given a set of existing plants and customer zones, our basic model identifies the optimal number and location of distribution centers and return centers assuming that all plants have remanufacturing capability. We devise a Lagrangian heuristic for this problem. The proposed solution method proved to be computationally efficient for solving large-scale instances of the closed-loop supply chain design problem. The potential benefits of the integrated model are demonstrated by comparing its results with those obtained from an alternative approach that determines optimal forward and ...

Discrete Applied Mathematics

Networks and Spatial Economics

In this study, a two-stage stochastic integer programming model is developed with a centralized p... more In this study, a two-stage stochastic integer programming model is developed with a centralized planning perspective to simultaneously address mitigation and response decisions in humanitarian logistics, where the mitigation decisions involve both building and transportation infrastructure retrofitting. The objective is to minimize the total cost of retrofitting, relief item transportation and relief item shortage under a limited mitigation budget. Due to the excessive number of binary decision variables, solving the model becomes computationally difficult. Therefore, we propose Lagrangean relaxation to decouple the overall model and solve it by Lagrangean heuristics. Computational results indicate the efficiency of the solution approaches in providing high quality feasible solutions to problem instances of realistic size and complexity.

Encyclopedia of Supply Chain Management, 2011

Topics Covered Include: Activity System Methodology Advanced Planning and Scheduling Overview Bal... more Topics Covered Include: Activity System Methodology Advanced Planning and Scheduling Overview Balancing Supply and Demand The Role of Benchmarking Bicycle Manufacturer's Internet Strategy: Case Study Buffer Management: Traditional and Simplified Theory of Constraints TOC Approach Business Practice and Performance Buyer Metrics for Performance Improvements: Case Study Capability Assessment Cash Flow and Performance Measures Cause and Vision Change Management Closed Loop Supply Chains Collaboration in Product Design Collaboration in Strategic Sourcing Collaboration with Partners in Design and Manufacturing Collaborative Relationships Templates Communications Management Competitive Advantage Compliance Program Constraints Management/Synchronization Container Security Continuous Improvement Imperative Corrupt Practices Act Cost Management Cost Reduction Cost Visibility Costing: Activity-Based by Retail Product CPFR Collaboration Model Corporate Social Responsibility and Strategy CTP/ATP Planning: Validation Customer Order Process Improvement Action Plans Customer Relationship Management Customer Service Moves to Proactive Matched Care Customer Value Assessment Demand Management Demand-Driven Supply Chain Design Principles for Remanufacturing Design: Case Study Dimensions of the Supply Chain Effort Discovery-Driven Planning Disposition Decisions for Recycled Products/Components Distributor's Role: Case Study Drivers of Change Drum-Buffer-Rope Emerging Partnership Model Enablers of Change Environmental Legislation Environmental Management and the Closed-Loop Supply Chain Evolution of Supply Chain Management Export Compliance Extended Product Design Failed Supply Chain Initiative: Case Study FDA/EPA Regulation FDA: Record Keeping Financial Analysis in Retailing Financial Performance Basics Flexibility Flexibility Sufficiency Flow versus Batch Forecasting Globalization Grading Recycled Products/Components Hardware Design Principles for Remanufacturing Hazardous Materials Hospital Reverse Supply Chain Case Study Human Resources Management Implementation: Manufacturing Plant Case Study Importation and Sourcing International Commercial Terms Information Technology as the Engine for Change Information Technology Project Innovation: Retail Change Driver Integration Management Inventory Management IT Best Practice Tools JIT and Pull Systems Keiretsu Network Roles for Technology Lean Supply Chain Consolidation Centers: Case Study Lean System Improvement Methodology Lean: Strengths and Limitations Levels of Supply Chain Maturity Linked Processes for Engineering and Manufacturing Little's Law for Material Flow Logistics Advanced Levels of Maturity Logistics Improvement Case Study Logistics Maturity at Levels 4 and 5 Logistics Models for Levels of Supply Chain Maturity Logistics Moves to Virtual Systems Maintenance, Repair, and Overhaul Operations: Case Study Market Environments Market for Remanufactured Products Market Mediation Costs Marketing, Sales, Customer Service Role Changes Materials Requirements Planning (MRP) Maturity Levels for Supply Chain Evolution Maturity Models Merchandise Budgeting: Financial Success in Retailing Merging Improvement Disciplines into SCM Metrics: Retail Supply Chains Models for Purchasing, Procurement, and Strategic Sourcing Motion Picture Industry Recycling Case Study MTA, MTS, MTO Issues Multi-Company Collaboration Multiple Supply Chains Operations-Centric Enable Processes Order Processing Organization Roadblocks: Project Failure Root Cause Partnership Types Partnership Templates Plan Communications Performance Measures and Structure PESTEL Planning and Control Systems Planning Supply Chain Execution Overview Port Security Program Pricing is a Special Problem Problem Solving Methodology Process Documentation Process Evaluation Process Improvement Implementation Process Links: Case Study Process Management Scope Process Standard Application Process Standards and Reference Models Process-Centered Management Processes and Systems Templates Procurement Management Product Design for Remanufacturing Product Life Cycles Product Take-Back and Recovery Practices Product Tracking: Retail Supply Chains Project and Process Innovation Project Management Project Process Template Projects Inputs and Outputs Purchasing Purchasing/Sourcing Transition from Tactical to Strategic Quality Control Tools Quality Function Deployment Quality Management Quality Standards Remanufacturing Retail Activity Systems and Process Definition Retail and Comparative Advantage Retail Businesses Retail Collaboration among Partners Retail Continuous Improvement Cycles Retail Decision Makers Retail Demand-Driven Tools and Techniques Retail Performance Retail Return Loops Retail Supply Chain Reverse Logistics Network Risk Management Root Cause for Cost S&OP Models Sarbanes-Oxley Scope Management SCOR Model Methodology Security and Compliance Implementation Security: Legislation, Acronyms, and Glossary Six Sigma Software…

Encyclopedia of Supply Chain Management, 2011

Encyclopedia of Supply Chain Management, 2011

In this paper, we study the capacitated squared Euclidean distance and general ℓp distance locati... more In this paper, we study the capacitated squared Euclidean distance and general ℓp distance location-allocation problem in the continuous space which seeks the optimum locations of facilities and the allocation of their products to customers. We propose a mixed-integer programming formulation for the problem. The proposed formulation gives the optimum solution for the rectilinear distance version and approximate solutions for

European Journal of Operational Research, 2016

In this paper, we consider the cargo mix problem under uncertainty in the container shipping indu... more In this paper, we consider the cargo mix problem under uncertainty in the container shipping industry. We seek to determine the optimal cargo mix in a multiperiod planning horizon with the objective of maximizing the total expected profit derived from all freight bookings received in the planning horizon. We present a two-stage stochastic integer programming model and propose a heuristic

Supply Chain Integration Modeling, Optimization and Application, 2010

Lecture Notes in Computer Science, 2010

We consider a problem in which a firm or franchise enters a market by locating new facilities whe... more We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff’s gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.

We focus on the order picking operation carried out in one of the major warehouses of a retailer ... more We focus on the order picking operation carried out in one of the major warehouses of a retailer to satisfy the orders placed by the stores of the same retailer. We investigate the simultaneous solution of the storage assignment problem and picker routing problem referred to as JSAPRP that involves both assigning items to storage locations and deciding on the routes of the pickers for item collection. The performance measure of interest is the minimization of the total traveling distance of the pickers. We develop a mathematical model which can only solve small instances of the JSAPRP. Therefore, we also devise a heuristic method based on adaptive large neighborhood search. Computational results obtained on numerous experiments reveal that the quality of the solutions produced by this heuristic is quite good.

European Journal of Operational Research

IISE Transactions

Abstract The Influence Maximization Problem has been widely studied in recent years, due to rich ... more Abstract The Influence Maximization Problem has been widely studied in recent years, due to rich application areas including marketing. It involves finding k nodes to trigger a spread such that the expected number of influenced nodes is maximized. The problem we address in this study is an extension of the reverse influence maximization problem, i.e., misinformation minimization problem where two players make decisions sequentially in the form of a Stackelberg game. The first player aims to minimize the spread of misinformation whereas the second player aims its maximization. Two algorithms, one greedy heuristic and one matheuristic, are proposed for the first player’s problem. In both of them, the second player’s problem is approximated by Sample Average Approximation, a well-known method for solving two-stage stochastic programming problems, that is augmented with a state-of-the-art algorithm developed for the influence maximization problem.

International Transactions in Operational Research

Future Generation Computer Systems

Abstract The popularity of traditional network services and web content is succeeded by the recen... more Abstract The popularity of traditional network services and web content is succeeded by the recent trend in customized services proliferated by the smart devices and gadgets. Fall-risk assessment, augmented reality, ECG (electrocardiography) monitoring, virtual reality-based gaming and similar services are driven through data generated by multi-modal sensors embedded in the end-user equipment. These services may possess varying characteristics and requirements represented with performance metrics and Quality of Service (QoS) parameters. Even though the small form-factor end-user gadgets are getting powerful in terms of resource capacity, they are still incapable of executing complex routines, and thus these tasks should be offloaded to a remote machine. Service-Centric Networks (SCN) focus on delivering customized services to the users in a location-independent fashion. This is in parallel with previous vision put forward by the Information-Centric Networks (ICN) and Content Delivery Networks (CDN), which aim to enhance the end-user experience. The novel set of services for complementing the daily activities of the end-users mostly depicts a latency-intolerant attribute which ultimately calls for a full-fledged resource allocation scheme. Within this context, both computation and networking resources should be allocated optimally, and task assignments should be handled precisely for following the requirements specified by the Service Level Agreements (SLAs). This paper initially presents and discusses problem definitions that should be addressed by the service-centric multi-tier computing architecture that is composed of edge, metro, and cloud servers. In order to achieve this objective, an SLA-aware optimal resource allocation and task assignment model for service-oriented networks is proposed. This optimization model is based on a nonlinear delay formulation for accommodating service-centric network scenarios under various conditions. It is then reshaped as a mixed-integer linear model through piecewise linear approximation. Additionally, a heuristic implementation is presented to address the time and space complexities of the problem for which the aforementioned optimization models remain ineffective. Performance evaluation results show that the proposed solutions are able to find a good allocation of resources while taking the requirements of the services into account.

Journal of Remanufacturing

Closed-loop supply chains involve forward flows of products from production facilities to custome... more Closed-loop supply chains involve forward flows of products from production facilities to customer zones as well as reverse flows from customer zones back to remanufacturing facilities. We present an integrated modeling framework for configuring a distribution system with reverse flows so as to minimize the total cost of satisfying customer demand and remanufacturing the returned items that are recoverable. Given a set of existing plants and customer zones, our basic model identifies the optimal number and location of distribution centers and return centers assuming that all plants have remanufacturing capability. We devise a Lagrangian heuristic for this problem. The proposed solution method proved to be computationally efficient for solving large-scale instances of the closed-loop supply chain design problem. The potential benefits of the integrated model are demonstrated by comparing its results with those obtained from an alternative approach that determines optimal forward and ...

Discrete Applied Mathematics

Networks and Spatial Economics

In this study, a two-stage stochastic integer programming model is developed with a centralized p... more In this study, a two-stage stochastic integer programming model is developed with a centralized planning perspective to simultaneously address mitigation and response decisions in humanitarian logistics, where the mitigation decisions involve both building and transportation infrastructure retrofitting. The objective is to minimize the total cost of retrofitting, relief item transportation and relief item shortage under a limited mitigation budget. Due to the excessive number of binary decision variables, solving the model becomes computationally difficult. Therefore, we propose Lagrangean relaxation to decouple the overall model and solve it by Lagrangean heuristics. Computational results indicate the efficiency of the solution approaches in providing high quality feasible solutions to problem instances of realistic size and complexity.

Encyclopedia of Supply Chain Management, 2011

Topics Covered Include: Activity System Methodology Advanced Planning and Scheduling Overview Bal... more Topics Covered Include: Activity System Methodology Advanced Planning and Scheduling Overview Balancing Supply and Demand The Role of Benchmarking Bicycle Manufacturer's Internet Strategy: Case Study Buffer Management: Traditional and Simplified Theory of Constraints TOC Approach Business Practice and Performance Buyer Metrics for Performance Improvements: Case Study Capability Assessment Cash Flow and Performance Measures Cause and Vision Change Management Closed Loop Supply Chains Collaboration in Product Design Collaboration in Strategic Sourcing Collaboration with Partners in Design and Manufacturing Collaborative Relationships Templates Communications Management Competitive Advantage Compliance Program Constraints Management/Synchronization Container Security Continuous Improvement Imperative Corrupt Practices Act Cost Management Cost Reduction Cost Visibility Costing: Activity-Based by Retail Product CPFR Collaboration Model Corporate Social Responsibility and Strategy CTP/ATP Planning: Validation Customer Order Process Improvement Action Plans Customer Relationship Management Customer Service Moves to Proactive Matched Care Customer Value Assessment Demand Management Demand-Driven Supply Chain Design Principles for Remanufacturing Design: Case Study Dimensions of the Supply Chain Effort Discovery-Driven Planning Disposition Decisions for Recycled Products/Components Distributor's Role: Case Study Drivers of Change Drum-Buffer-Rope Emerging Partnership Model Enablers of Change Environmental Legislation Environmental Management and the Closed-Loop Supply Chain Evolution of Supply Chain Management Export Compliance Extended Product Design Failed Supply Chain Initiative: Case Study FDA/EPA Regulation FDA: Record Keeping Financial Analysis in Retailing Financial Performance Basics Flexibility Flexibility Sufficiency Flow versus Batch Forecasting Globalization Grading Recycled Products/Components Hardware Design Principles for Remanufacturing Hazardous Materials Hospital Reverse Supply Chain Case Study Human Resources Management Implementation: Manufacturing Plant Case Study Importation and Sourcing International Commercial Terms Information Technology as the Engine for Change Information Technology Project Innovation: Retail Change Driver Integration Management Inventory Management IT Best Practice Tools JIT and Pull Systems Keiretsu Network Roles for Technology Lean Supply Chain Consolidation Centers: Case Study Lean System Improvement Methodology Lean: Strengths and Limitations Levels of Supply Chain Maturity Linked Processes for Engineering and Manufacturing Little's Law for Material Flow Logistics Advanced Levels of Maturity Logistics Improvement Case Study Logistics Maturity at Levels 4 and 5 Logistics Models for Levels of Supply Chain Maturity Logistics Moves to Virtual Systems Maintenance, Repair, and Overhaul Operations: Case Study Market Environments Market for Remanufactured Products Market Mediation Costs Marketing, Sales, Customer Service Role Changes Materials Requirements Planning (MRP) Maturity Levels for Supply Chain Evolution Maturity Models Merchandise Budgeting: Financial Success in Retailing Merging Improvement Disciplines into SCM Metrics: Retail Supply Chains Models for Purchasing, Procurement, and Strategic Sourcing Motion Picture Industry Recycling Case Study MTA, MTS, MTO Issues Multi-Company Collaboration Multiple Supply Chains Operations-Centric Enable Processes Order Processing Organization Roadblocks: Project Failure Root Cause Partnership Types Partnership Templates Plan Communications Performance Measures and Structure PESTEL Planning and Control Systems Planning Supply Chain Execution Overview Port Security Program Pricing is a Special Problem Problem Solving Methodology Process Documentation Process Evaluation Process Improvement Implementation Process Links: Case Study Process Management Scope Process Standard Application Process Standards and Reference Models Process-Centered Management Processes and Systems Templates Procurement Management Product Design for Remanufacturing Product Life Cycles Product Take-Back and Recovery Practices Product Tracking: Retail Supply Chains Project and Process Innovation Project Management Project Process Template Projects Inputs and Outputs Purchasing Purchasing/Sourcing Transition from Tactical to Strategic Quality Control Tools Quality Function Deployment Quality Management Quality Standards Remanufacturing Retail Activity Systems and Process Definition Retail and Comparative Advantage Retail Businesses Retail Collaboration among Partners Retail Continuous Improvement Cycles Retail Decision Makers Retail Demand-Driven Tools and Techniques Retail Performance Retail Return Loops Retail Supply Chain Reverse Logistics Network Risk Management Root Cause for Cost S&OP Models Sarbanes-Oxley Scope Management SCOR Model Methodology Security and Compliance Implementation Security: Legislation, Acronyms, and Glossary Six Sigma Software…

Encyclopedia of Supply Chain Management, 2011

Encyclopedia of Supply Chain Management, 2011

In this paper, we study the capacitated squared Euclidean distance and general ℓp distance locati... more In this paper, we study the capacitated squared Euclidean distance and general ℓp distance location-allocation problem in the continuous space which seeks the optimum locations of facilities and the allocation of their products to customers. We propose a mixed-integer programming formulation for the problem. The proposed formulation gives the optimum solution for the rectilinear distance version and approximate solutions for

European Journal of Operational Research, 2016

In this paper, we consider the cargo mix problem under uncertainty in the container shipping indu... more In this paper, we consider the cargo mix problem under uncertainty in the container shipping industry. We seek to determine the optimal cargo mix in a multiperiod planning horizon with the objective of maximizing the total expected profit derived from all freight bookings received in the planning horizon. We present a two-stage stochastic integer programming model and propose a heuristic

Supply Chain Integration Modeling, Optimization and Application, 2010

Lecture Notes in Computer Science, 2010

We consider a problem in which a firm or franchise enters a market by locating new facilities whe... more We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff’s gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.