new optimization model for the tactical design of scheduled service networks for transportation syst
emission cost estimates do not seem to be as important as fuel or labor costs. ? High variation in customer demand implies more room for reducing energy. ? The use of fewer vehicles generally implies lower fuel consumption.
144
Logistics service provider–client relationships Original Research Article
Transportation Research Part E: Logistics and Transportation Review, Volume 41, Issue 3, May 2005, Pages 179-200
Photis M. Panayides, Meko So
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The paper investigates the effects of relationship orientation in the logistics service provider–client interaction. A conceptual model is developed and six research hypotheses are empirically analysed using structural equation modelling. The results indicate that relationship orientation has a positive influence on key organisational capabilities, like organisational learning and innovation, promoting an improvement in supply chain effectiveness and performance. Theoretical, managerial and research implications are discussed.
Article Outline
1. Introduction
2. Logistic service provider–client relationships
3. Theory and research hypotheses
3.1. Conceptual model and construct definitions
3.2. Hypotheses
4. Methodology
4.1. Construct operationalisation
4.2. Sampling and data collection
4.3. Construct testing
5. Empirical analysis and results
5.1. Descriptive statistics and analysis of the measurement model
5.2. The structural models and hypothesis testing
6. Discussion and implications
6.1. Theoretical implications
6.2. Limitations and further research
6.3. Managerial implications
7. Conclusion
Appendix A. Appendix
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145
Periodic airline fleet assignment with time windows, spacing constraints, and time dependent revenues Original Research Article
European Journal of Operational Research, Volume 175, Issue 3, 16 December 2006, Pages 1754-1766
Nicolas Bélanger, Guy Desaulniers, Fran?ois Soumis, Jacques Desrosiers
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Given the sets of flights and aircraft of an airline carrier, the fleet assignment problem consists of assigning the most profitable aircraft type to each flight. In this paper we propose a model for the periodic fleet assignment problem with time windows in which departure times are also determined. Anticipated profits depend on the schedule and the selection of aircraft types. In addition, short spacings between consecutive flights which serve the same origin–destination pair of airports are penalized. We propose a non-linear integer multi-commodity network flow formulation. We develop new branch-and-bound strategies which are embedded in our branch-and-price solution strategy. Finally, we present computational res
ults for periodic daily schedules on three real-world data sets.
Article Outline
1. Introduction
2. Problem description
3. Literature review
4. A mathematical model
4.1. A multi-commodity network structure
4.2. A mathematical formulation
5. Column generation
6. Branch-and-bound strategies
7. Computational experiments
7.1. Parameters and statistics
7.2. Results
8. Conclusion
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146
A Lagrangian relaxation approach for a multi-mode inventory routing problem with transshipment in crude oil transportation Original Research Article
Computers & Chemical Engineering, In Press, Corrected Proof, Available online 12 January 2011
Qingning Shen, Feng Chu, Haoxun Chen
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An inventory routing problem in crude oil transportation is studied, in which crude oil is transported from a supply center to multiple customer harbors to satisfy their demands over multiple periods. In the problem, a heterogeneous fleet of tankers consisting of tankers owned by a distributor and tankers rented from a third party, a pipeline, and multiple types of routes are considered; both inventory level and shortage level at each customer harbor are limited. The objective is to determine for each period over a given time horizon the number of tankers of each type to be rented/returned at the supply center, the number of tankers of each type to be dispatched on each route, and the quantity of crude oil flowing through the pipeline that minimizes the total logistics cost.
After formulating the problem as a mixed integer programming problem, a Lagrangian relaxation approach is developed for finding a near optimal solution of the problem. The approach is also applied to a variant of the problem in which both fully and partially loaded tankers are allowed in the transportation of crude oil. Numerical experiments show that this approach outperforms an existing meta-heuristic algorithm, especially for the instances of large sizes.
Article Outline
1. Introduction
2. Problem description and notation
3. Mathematical model
4. Lagrangian relaxation approach
4.1. Relaxation scheme
4.2. Resolution of the subproblems
4.2.1. Subproblem IR
4.2.2. Subproblem NF
4.3. Resolution of the Lagrangian dual problem
5. Construction and evaluation of feasible solutions
5.1. Construction of a feasible solution
5.2. Evaluation of feasible solutions
6. Lagrangian relaxation approach to a variant of the crude oil transportation problem
7. Numerical results
7.1. Results for model COTP
7.2. Results for model COTPV
8. Conclusion
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147
Manufacturer’s coordination mechanism for single-period supply chain problems with fuzzy demand Original Research Article
Mathematical and Computer Modelling, Volume 51, Issues 5-6, March 2010, Pages 693-699
Ruoning Xu, Xiaoy
an Zhai
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In this paper, we consider the coordination problem for single-period supply chain problems with fuzzy demand. An efficient coordination mechanism is designed from the manufacturer’s point of view. By setting different wholesale prices for different order quantities, the manufacturer can induce the retailer to order the right quantity, and therefore realize the maximum supply chain profit. It is shown that both the manufacturer and the retailer can benefit from the coordination by choosing the sharing proportion in an appropriate interval.
Article Outline
1. Introduction
2. Preliminaries
3. Manufacturer’s coordination mechanism
4. Conclusion
Acknowledgements
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148
Understanding the psychological process underlying customer satisfaction and retention in a relational service Original Research Article
Journal of Business Research, Volume 62, Issue 11, November 2009, Pages 1152-1159
Lin Guo, Jing Jian Xiao, Chuanyi Tang
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This paper reexamines the psychological process underlying the relationship between customer satisfaction and customer retention in a relational service context. It is based on a composite model of the attitude-behavior relation, which takes both attitude toward target and attitude toward behavior into account. Data were collected from a survey with a sample of 209 clients from a major credit counseling organization in the USA. Account data indicating those clients' actual retention behavior were matched with the survey data. A two-step structural equation modeling (SEM) procedure was employed to establish the construct validity and test the hypotheses. The results revealed that the effect of customer satisfaction on retention is mediated by the more proximal determinants of the actual retention behavior. Specifically, customer satisfaction has both direct and indirect effects on customers' attitudes toward remaining in the Debt Management Program (DMP), which is the proximal predictor of customer retention. In addition, satisfaction alone cannot guarantee customer retention. Customers' perceived behavioral control exerts direct effects on their intention to remain and retention.
Article Outline
1. Introduction
2. Theoretical framework
2.1. Customer's overall satisfaction with the organization as attitude toward target
2.2. The relationship between attitude toward target and attitude toward behavior
2.3. The role of perceived behavioral control
3. Hypotheses development
3.1. The validity of the theory of planned behavior in predicting customer retention
3.2. The psychological process underlying customer satisfaction and attitude toward remaining
3.3. The i
nfluence of perceived behavioral control on satisfaction with the organization
3.4. The full mediating effect of TRA components
4. Methodology
4.1. Sample
4.2. Measurement
5. Analysis and results
5.1. Measurement model testing and results
5.2. Overall structural model and hypotheses testing
6. Conclusion and discussion
7. Limitations and future research
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149
A heuristic for single-warehouse multiretailer supply chains with all-unit transportation cost discounts Original Research Article
European Journal of Operational Research, Volume 187, Issue 2, 1 June 2008, Pages 473-482
James Hill, Michael Galbreth
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In supply chain management research, transportation costs, if explicitly considered at all, are frequently assumed to be linear. These costs often have a more complex form, such as an all-unit discount structure – this piecewise cost function adds significant complexity when included in supply chain management problems and is therefore often ignored due to solution time or tractability concerns. We present and evaluate a new heuristic procedure which provides good solutions to problems involving all-unit discount cost functions while significantly reducing solution times. The general nature of this procedure does not require assumptions about the supply chain structure or policies, and is therefore applicable in a wide range of settings.
Article Outline
1. Introduction
2. Literature review
3. All-unit discount cost function
4. Problem formulation
5. A geometric approximation and solution procedure
5.1. Step 1: Linear approximation
5.2. Step 2: Solve the simplified MIP
5.3. Step 3: Search for improved solutions
6. Numerical results
7. Conclusions
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150
The impact of supply chain integration on performance: A contingency and configuration approach Original Research Article
Journal of Operations Management, Volume 28, Issue 1, January 2010, Pages 58-71
Barbara B. Flynn, Baofeng Huo, Xiande Zhao
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This study extends the developing body of literature on supply chain integration (SCI), which is the degree to which a manufacturer strategically collaborates with its supply chain partners and collaboratively manages intra- and inter-organizational processes, in order to achieve effective and efficient flows of products and services, information, money and decisions, to provide maximum value to the customer. The previous research is inconsistent in its findings about the relationship between SCI and performance. We attribute this inconsistency to incomplete definitions of SCI, in particular, the tendency to focus on customer and supplier integrat
ion only, excluding the important central link of internal integration. We study the relationship between three dimensions of SCI, operational and business performance, from both a contingency and a configuration perspective. In applying the contingency approach, hierarchical regression was used to determine the impact of individual SCI dimensions (customer, supplier and internal integration) and their interactions on performance. In the configuration approach, cluster analysis was used to develop patterns of SCI, which were analyzed in terms of SCI strength and balance. Analysis of variance was used to examine the relationship between SCI pattern and performance. The findings of both the contingency and configuration approach indicated that SCI was related to both operational and business performance. Furthermore, the results indicated that internal and customer integration were more strongly related to improving performance than supplier integration.
Article Outline
1. Introduction
2. Theoretical background
2.1. Definition of SCI
2.2. Dimensions of SCI
2.3. Contingency approach to SCI
2.3.1. Relationship between internal integration and performance
2.3.2. Relationship of customer and supplier integration to performance
2.3.3. Moderating effects
2.4. Configuration approach
2.4.1. Configurations of SCI
2.4.2. Impact of SCI patterns on performance
3. Research methodology
3.1. Questionnaire design and measures
3.2. Sampling and data collection
3.3. Reliability and validity
4. Results
4.1. Contingency analysis of SCI
4.2. Configuration analysis of SCI
4.2.1. Emergent taxonomy of SCI
4.2.2. Relationship between SCI patterns and performance
5. Discussion
6. Conclusions and limitations
Acknowledgements
Appendix A. Summary of prior literature on the relationship between SCI and performance
Appendix B. Measurement items (with factor loadings)
References
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151
Redesigning a warehouse network Original Research Article
European Journal of Operational Research, Volume 176, Issue 1, 1 January 2007, Pages 210-229
Emanuel Melachrinoudis, Hokey Min
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To take advantage of economies of scale, a growing number of firms have begun to explore the possibility of integrating supply chain activities. The advent of such a possibility would necessitate the redesign of a warehouse network. Typically, a warehouse redesign problem involves the consolidation of regional warehouses into a fewer number of master stocking points and the subsequent phase-out of redundant or underutilized warehouses without deteriorating customer services. This paper develops a mixed-integer programming model to solve the warehouse redesign problem. The usefulness of the model was validated by its successful application to a real-world problem and by its sensitivity analyses when us
ed with changing scenarios within a warehouse network configuration.
Article Outline
1. Introduction
2. Problem definition
3. Model design
3.1. Indices and sets
3.2. Model parameters
3.3. Decision variables
3.4. Mathematical formulation
3.5. Upper bound on nonunique customer demand allocations
3.6. Estimation of cost parameters
4. Model application and results
5. Sensitivity analyses
6. Lessons learned from model implementation
7. Concluding remarks and future research directions
Acknowledgements
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152
Inventory constrained maritime routing and scheduling for multi-commodity liquid bulk, Part I: Applications and model Original Research Article
European Journal of Operational Research, Volume 176, Issue 1, 1 January 2007, Pages 106-130
Faiz Al-Khayyal, Seung-June Hwang
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This paper formulates a model for finding a minimum cost routing in a network for a heterogeneous fleet of ships engaged in pickup and delivery of several liquid bulk products. The problem is frequently encountered by maritime chemical transport companies, including oil companies serving an archipelago of islands. The products are assumed to require dedicated compartments in the ship. The problem is to decide how much of each product should be carried by each ship from supply ports to demand ports, subject to the inventory level of each product in each port being maintained between certain levels that are set by the production rates, the consumption rates, and the storage capacities of the various products in each port. This important and challenging inventory constrained multi-ship pickup–delivery problem is formulated as a mixed-integer nonlinear program. We show that the model can be reformulated as an equivalent mixed-integer linear program with special structure. Over 100 test problems are randomly generated and solved using CPLEX 7.5. The results of our numerical experiments illuminate where problem structure can be exploited in order to solve larger instances of the model. Part II of the sequel will deal with new algorithms that take advantage of model properties.
Article Outline
1. Introduction
2. Maritime routing and scheduling literature
3. Multi-commodity bulk shipping
4. Model formulation
4.1. Routing constraints
4.1.1. Initial position constraints
4.1.2. Flow conservation constraints
4.1.3. Route finishing constraints
4.1.4. One time visit constraints
4.1.5. Arrival sequence constraints
4.2. Constraints for loading and discharging
4.2.1. Ship load constraints
4.2.2. Initial ship load constraints
4.2.3. Compartment capacity constraints
4.2.4. Servicing product constraints
4.3. Constraints for time aspects
4.3.1. Service time sequence constraints
4.3.2. Service finishing time constraints
4.3.3. Route and schedule compatibility constraints
4.4. Constraints for the inventories
4.4.1. Initial inventory constraints
4.4.2. Inventory level constraints
4.4.3. Stock level constraints
4.4.4. Stock level bounds
4.5. Objective function
5. Linear reformulation
5.1. Linearizing ship load constraints
5.2. Linearizing route and schedule compatibility constraints
5.3. Linearizing stock level constraints
5.4. Linearizing stock level bounds constraints
6. Mixed integer linear programming formulation
6.1. Example
6.2. Computing time
7. Concluding remarks
Acknowledgements
Appendix A. Glossary of notation
A.1. Variables
A.2. Sets
A.3. Parameters
Appendix B. General statement and proof of Proposition 2
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153
Research on warehouse design and performance evaluation: A comprehensive review Review Article
European Journal of Operational Research, Volume 203, Issue 3, 16 June 2010, Pages 539-549
Jinxiang Gu, Marc Goetschalckx, Leon F. McGinnis
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This paper presents a detailed survey of the research on warehouse design, performance evaluation, practical case studies, and computational support tools. This and an earlier survey on warehouse operation provide a comprehensive review of existing academic research results in the framework of a systematic classification. Each research area within this framework is discussed, including the identification of the limits of previous research and of potential future research directions.
Article Outline
1. Introduction
2. Warehouse design
2.1. Overall structure
2.2. Sizing and dimensioning
2.2.1. Warehouse sizing
2.2.2. Warehouse dimensioning
2.3. Department layout
2.3.1. Pallet block-stacking pattern (P1)
2.3.2. Storage department layout (P2)
2.3.3. AS/RS configuration (P3)
2.4. Equipment selection
2.5. Operation strategy
2.5.1. Storage
2.5.2. Order picking
3. Performance evaluation
3.1. Benchmarking
3.2. Analytical models
3.2.1. Aisle based models
3.2.2. Integrated models
4. Case studies
5. Computational systems
6. Conclusions and discussion
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154
The vehicle routing problem in field logistics part I Original Research Article
Biosystems Engineering, Volume 104, Issue 4, December 2009, Pages 447-457
D.D. Bochtis, C.G. S?rensen
Close preview | Related articles | Related reference work articles AbstractAbstract | Figures/TablesFigures/Tables | ReferencesReferencesThe vehicle routing problem (VRP) has been characterised as one of the great success stories of operational research, providing and facilitating, for over fifty years, optimal planning solutions for vehicle fleets in a large number of real-life applications. In its simplest form, a VRP can be described as the problem of determining least-cost routes from one depot to a set of geographically dispersed “customers” (such as c
ities, stores, warehouses, and schools). VRP constitutes one of the most challenging combinatorial optimisation problems. A large number of different approaches have been developed over the years and a number of software packages are available on the market. In the agriculture, the VRP has only very recently been applied to the planning and execution of in-field operations, despite the fact that almost all agricultural field operations (AFO) inherently involve the motion of vehicles.
In this paper, a dedicated classification of AFO is devised and tailored to a conceptual application of the VRP within the domain of agricultural field logistics. The concept regards the operations of primary agricultural machines, with the worked tracks in the field representing the “customers” using VRP methodology. By casting the agricultural fleet management problem in the framework of well-known VRP instances, over half a century of research and implementation experience can be brought to bear on the problem. This will provide for the enhanced management of conventional machinery systems, as well as, the mission and route-planning aspects of the high level control of emerging field robots.
Article Outline
Nomenclature
1. Introduction
2. Preliminaries
2.1. VRP notations
2.2. Definitions
3. Casting agricultural field operations into examples of vehicle routing problem
3.1. Graphical representation
3.2. Node demand
3.3. Arc cost assignment
3.4. Application of vehicle routing problem instances to agricultural field operations
3.4.1. Single PU in an NMF operation
3.4.2. Multiple-PU in NMF operations
3.4.3. Single PU in a deterministic IMF operation using a single stationary FU
3.4.4. Multiple identical PUs in a deterministic IMF operation using a single stationary FU
3.4.5. Multiple non-identical PUs in a deterministic IMF operation using a single stationary FU
3.4.6. Single PU in a stochastic OMF or IMF operation using a single stationary FU
3.4.7. Multiple PUs in OMF or stochastic IMF operation using one or multiple stationary FU
3.4.8. Summary
4. Discussion
5. Conclusions
Appendices. Appendix
Appendix I: Graph connectivity
Appendix II: Node sequence to track sequence transformation
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155
Network flow-based approaches for integrated aircraft fleeting and routing Original Research Article
European Journal of Operational Research, Volume 193, Issue 2, 1 March 2009, Pages 591-599
Mohamed Haouari, Najla Aissaoui, Farah Zeghal Mansour
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Given a schedule of flights to be flown, the aircraft fleeting and routing problem (AFRP) consists of determining a minimum-cost route assignment for each aircraft so as to cover each flight by exactly one aircraft while satisfying maintenance requirements and other activity constraints. We investigate network flo
w-based heuristic approaches for this problem. Computational experiments conducted on real-data given by TunisAir show that the proposed heuristic consistently yields very near-optimal solutions while requiring modest CPU effort.
Article Outline
1. Introduction
2. Literature review
3. A 0–1 programming formulation and lower bound computation
3.1. Notation
3.2. A multi-commodity network flow formulation
3.3. A Lagrangian lower bound
4. A two-phase network flow-based heuristic
4.1. Phase 1 – building an initial solution by solving successive linear assignment problems
4.2. Phase 2 – building an improved solution by solving minimum-cost flow problems
5. Computational results
6. Conclusion
Acknowledgements
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156
A Lagrangian relaxation-based heuristic for the vehicle routing with full container load Original Research Article
European Journal of Operational Research, Volume 176, Issue 1, 1 January 2007, Pages 87-105
Akio Imai, Etsuko Nishimura, John Current
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We address a problem of vehicle routing that arises in picking up and delivering full container load from/to an intermodal terminal. The substantial cost and time savings are expected by efficient linkage between pickup and delivery tasks, if the time of tasks and the suitability of containers for cargo allow. As this problem is NP-hard, we develop a subgradient heuristic based on a Lagrangian relaxation which enables us to identify a near optimal solution. The heuristic consists of two sub-problems: the classical assignment problem and the generalized assignment problem. As generalized assignment problem is also NP-hard, we employ an efficient solution procedure for a bin packing based problem, which replaces the generalized assignment problem. The heuristic procedure is tested on a wide variety of problem examples. The test results demonstrate that the procedure developed here can efficiently solve large instances of the problem.
Article Outline
1. Introduction
2. Problem description
3. Related literature
4. Problem formulation and Lagrangian relaxation
4.1. Problem formulation
4.2. Lagrangian relaxation
5. Solution procedure
5.1. Lower bound and feasible solution
5.2. Entire solution procedure
6. Numerical experiments
7. Concluding remarks
Acknowledgements
Appendix A. Heuristic for the GBPP
Appendix B. The subgradient procedure
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157
Inter-organizational relationships and information sharing in supply chains Original Research Article
International Journal of Information Management, In Press, Corrected Proof, Available online 20 November 2010
Jao-Hong Cheng
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158
Leveraging the supply chain flexibility of third party logistics
– Hybrid knowledge-based system approach Original Research Article
Expert Systems with Applications, Volume 35, Issue 4, November 2008, Pages 1998-2016
K.L. Choy, Harry K.H. Chow, K.H. Tan, Chi-Kin Chan, Esmond C.M. Mok, Q. Wang
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159
A decision support system for integrated hazardous materials routing and emergency response decisions Original Research Article
Transportation Research Part C: Emerging Technologies, Volume 16, Issue 6, December 2008, Pages 684-703
Konstantinos G. Zografos, Konstantinos N. Androutsopoulos
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160
Benefits of traffic engineering using QoS routing schemes and network controls Original Research Article
Computer Communications, Volume 27, Issue 5, 20 March 2004, Pages 387-399
Shekhar Srivastava, Balaji Krithikaivasan, Cory Beard, Deep Medhi, Appie van de Liefvoort, Wesam Alanqar, Ananth Nagarajan
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161
A goal programming approach to vehicle routing problems with soft time windows Original Research Article
European Journal of Operational Research, Volume 177, Issue 3, 16 March 2007, Pages 1720-1733
Herminia I. Calvete, Carmen Galé, María-José Oliveros, Belén Sánchez-Valverde
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162
The effects of technological turbulence and breadth on supply chain technology acceptance and adoption Original Research Article
Journal of Operations Management, Volume 28, Issue 6, November 2010, Pages 522-536
Chad W. Autry, Scott J. Grawe, Patricia J. Daugherty, R. Glenn Richey
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163
A competitive, charter air-service planning model for student athlete travel Original Research Article
Transportation Research Part B: Methodological, Volume 45, Issue 1, January 2011, Pages 128-149
Gautam Gupta, Anne Goodchild, Mark Hansen
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164
Service network design with management and coordination of multiple fleets Original Research Article
European Journal of Operational Research, Volume 193, Issue 2, 1 March 2009, Pages 377-389
Jardar Andersen, Teodor Gabriel Crainic, Marielle Christiansen
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