Capacitated Lot Sizing Problems in Process Industries (eBook)

Ramya Ravi currently works in Caterpillar India Private Limited at Chennai, India. She completed Bachelor of Engineering in Electrical and Electronics Engineering at Sri Chandrasekharendra Saraswati Viswa Mahavidhyala University in 2008. She completed Master of Engineering in Industrial Engineering at Thiagarajar College of Engineering, Madurai (Anna University) in 2011. Thereafter, she received Ph.D. in Operations Management from IIT Madras in 2017. Her research interests include Supply Chain Management, Inventory Optimization, Production Planning and Scheduling, and Analytics. She has a publication in International Journal of Production Research, and she has attended international conferences, both in India and abroad. Chandrasekharan Rajendran is a Professor in the Department of Management Studies at IIT Madras, India. He holds RAGS Family Foundation Institute Chair in IIT Madras. He has been serving on the faculty of IIT Madras since 1987. His research interests include Operations and Supply Chain Management, Logistics and Distribution Management, Scheduling in Manufacturing and Service Systems, Optimization and Heuristic Techniques, Simulation Modeling, and Quality Management. He is a recipient of Alexander von Humboldt Research Fellowship of Germany and he is also a Visiting Professor in University of Passau, Germany. He has been conferred Dr. rer. pol. h.c. (Doctor of Business Administration and Economics (Honoris Causa)) by University of Passau for his outstanding achievements and contributions to research. He has been ranked among the best researchers, both in India and world-wide, in Operations Management. Hans Ziegler has his Diploma from University of Karlsruhe (TH) (now called Karlsruhe Institute of Technology), and PhD and Post-doctoral Habilitation from University of Paderborn. He had been on the faculty of Universities of Paderborn and Darmstadt, before moving to University of Passau where he holds the Chair for Production, Operations and Logistics Management (since 1991). He has research interests in Operations Research, Production and Operations Management, Supply Chain and Logistics Management, Scheduling in Manufacturing and Service Systems, and Inventory Management. Prof. Ziegler has publications in many renowned international journals such as Computers and Industrial Engineering, Computers and Operations Research, Engineering Costs and Production Economics, European Journal of Operational Research, International Journal of Advanced Manufacturing and Technology, International Journal of Production Research, Production Planning and Control, Operations Research Letters, OR Spektrum, and Zeitschrift fuer Operations Research.Sanjay Mohapatra received his B.E. from NIT Rourkela, M.Tech from IIT Madras, PGDBM XIMB, India and has finished his Ph.D. from Utkal University, India under Management Department. At present, he is an Associate Professor in Information Systems in XIMB, India. Professor Mohapatra has more than 21 years of industry experience. He has worked in various capacities in organizations like Hindustan Aeronautics Limited, Larsen & Toubro, PricewaterHouse, Infosys, Polaris & J&B Software. His teaching interests are in IT Strategy and Management Information Systems and research interests are in the area of IT enabled processes. He has authored/co-authored nine books and more than twenty papers in peer reviewed international journals.Dr. K.Ganesh is Senior Knowledge Expert and Global Lead of “supply chain management center of competence” at McKinsey & Company, Chennai, India. He has graduated in Production Engineering from Annamalai University with the university first rank. He pursued his Masters’ degree in Industrial Engineering at NIT Trichy and secured college first. He then moved to IIT Madras where he obtained his doctoral degree in Supply Chain. He is having total 14 years of research and consulting experience in the supply chain consulting and worked with top consulting firms such as TCS and IBM. He has published more than 100 papers in leading international research and written 10 international books. He is himself a lyricist and has written several poems in both English and Tamil.

Preface 6
Contents 8
List of Tables 11
List of Figures 13
Abbreviations 17
Notations 19
1 Introduction 34
1.1 Preamble to the Production Planning Problem 34
1.2 Basic Characteristics and Attributes of Lot Sizing Models 35
1.2.1 Time Based Characteristics and Attributes 35
Planning Horizon 36
Time Scale 36
Parameters/Data 36
Objective Function 36
Cost Components 36
Capacity 36
Number of Resources 37
Setup Operation 37
1.2.2 Product Based Characteristics and Attributes 37
Number of Products 37
Inventory Restrictions 37
Service Policy 38
1.3 Classification of Lot Sizing Models 38
1.3.1 Continuous Lot Sizing Problem: Economic Lot Scheduling Problem (ELSP) 38
1.3.2 Dynamic Lot Sizing Problem 38
Uncapacitated Lot Sizing Problem 38
Capacitated Lot Sizing Problem 39
Small Bucket Lot Sizing Models 39
Big Bucket Lot Sizing Models 40
1.4 An Analysis of Lot Sizing Literature 43
1.4.1 Literature on CLSP Without Production Carryover Across Periods and Without Sequence Dependent Setups 44
1.4.2 Literature on CLSP Without Production Carryover Across Periods and with Sequence Dependent Setups 50
1.4.3 Literature on CLSP with Production Carryover Across Periods and Without Sequence Dependent Setups 52
CLSP with Production Carryover Across Periods and Setup Splitting Between Two Periods 56
CLSP with Production Carryover Across Periods and Setup Crossover Across Many Periods 59
1.4.4 Literature on CLSP with Production Carryover Across Periods and with Sequence Dependent Setups 59
1.5 Integrated Decision Making in Supply Chains 63
1.6 Summary 64
2 CLSP: Real Life Applications and Motivation to Study Lot Sizing Problems in Process Industries 65
2.1 Production Planning in Discrete Manufacturing Industries and Continuous Manufacturing Industries 65
2.1.1 Discrete Manufacturing Industries 65
2.1.2 Continuous Manufacturing Industries 65
Batch Process Industries 66
Die Casting Industry 66
Rubber Accessories Manufacturing Industry 67
Flow/Continuous Process Industries 67
Paper and Pulp Industry 67
Planning of Beverage Production 68
Cement Manufacturing Process 68
Food Processing Industry 69
Continuous Casting of Steel Plates 70
Planning of Production of Glass Containers 70
Process of Sugar Manufacturing 70
2.2 Further Motivation from a Real-Life Case Study 72
2.3 Scope of the Book in the Context of Process Industries 73
2.4 Summary 77
3 Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods (CLSP:PCSC): Mathematical Model 1 (MM1) and a Heuristic for Process Industries 78
3.1 Introduction and Problem Definition 78
3.2 Basic Assumptions of the Proposed Mathematical Model (MM1:CLSP-PCSC) 83
3.3 Mathematical Model (MM1:CLSP-PCSC) for the Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods 84
3.3.1 Parameters/Indices 84
3.3.2 Decision Variables 85
3.3.3 Mathematical Model 1 (MM1:CLSP-PCSC) 86
3.3.4 Method of Tracking Setups in MM1:CLSP-PCSC 95
3.4 Special Cases of CLSP-PCSC with Respect to MM1:CLSP-PCSC 95
3.4.1 Setup Cost of a Product Calculated with Respect to the Period of Its Setup Completion 95
3.4.2 Setup Cost and Holding Cost of a Product Being Time Independent 96
3.5 Numerical Illustrations and Discussion with Respect to MM1:CLSP-PCSC 96
3.5.1 Setup Cost of a Product Calculated with Respect to the Period of Its Setup Initiation 97
3.5.2 Setup Cost of a Product Calculated with Respect to the Period of Its Setup Completion 97
3.5.3 Setup Cost and Holding Cost of a Product Being Time Independent 98
3.5.4 Observations from an Existing Model 98
3.6 Proposed Heuristic for CLSP-PCSC with Respect to MM1:CLSP-PCSC 104
3.7 Computational Experience 111
3.7.1 Comparing Solution Times of the Proposed Mathematical Models (MM1:CLSP-PCSC) 111
3.7.2 Comparison of Exact and Heuristic Approaches of MM1:CLSP-PCSC 112
3.8 Summary 133
4 Further Development: Mathematical Model 2 (MM2) and a Comprehensive Heuristic for Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods for Process Industries 134
4.1 Introduction and Problem Definition 134
4.2 Basic Assumptions of the Proposed Mathematical Model (MM2:CLSP-PCSC) 136
4.3 Mathematical Model 2 (MM2:CLSP-PCSC) for the Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods 137
4.3.1 Parameters/Indices 137
4.3.2 Decision Variables 138
4.3.3 Mathematical Model 2 (CLSP-PCSC) 139
4.3.4 Method of Tracking Setups in MM2:CLSP-PCSC 147
4.4 Special Cases of CLSP-PCSC with Respect to MM2:CLSP-PCSC 147
4.4.1 Setup Cost of a Product Calculated with Respect to the Period of Its Setup Completion 147
4.4.2 Setup Cost and Holding Cost of a Product Being Time Independent 149
4.5 Numerical Illustrations and Discussion with Respect to MM2:CLSP-PCSC 149
4.5.1 Setup Cost of a Product Calculated with Respect to the Period of Its Setup Initiation 151
4.5.2 Setup Cost of a Product Calculated with Respect to the Period of Its Setup Completion 151
4.5.3 Setup Cost and Holding Cost of a Product Being TimeIndependent 151
4.6 Proposed Heuristic for CLSP-PCSC with Respect to MM2:CLSP-PCSC 154
4.7 Computational Experience 157
4.8 Summary 161
5 Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods Assuming Sequence-Dependent Setup Times and Setup Costs (CLSP-SD-PCSC): Mathematical Models for Process Industries 162
5.1 Introduction and Problem Definition 162
5.2 Basic Assumptions of the Proposed Mathematical Models (MM1:CLSP-SD-PCSC and MM2:CLSP-SD-PCSC) 165
5.3 Mathematical Model 1 (MM1:CLSP-SD-PCSC) 166
5.3.1 Parameters/Indices 166
5.3.2 Decision Variables 167
5.3.3 Mathematical Model 1 (MM1:CLSP-SD-PCSC) 169
5.4 Mathematical Model 2 (MM2:CLSP-SD-PCSC) 181
5.4.1 Parameters/Indices 181
5.4.2 Decision Variables 181
5.4.3 Mathematical Model 2 (MM2:CLSP-SD-PCSC) 186
5.5 A Numerical Illustration and Discussion 206
5.6 Computational Experience 211
5.7 Summary 213
6 Summary Concerning Theoretical Developments 214
References 218