Alexandre Dolgui

A stochastic model for operating room planning with elective and emergency demand for surgery

This paper describes a stochastic model for Operating Room (OR) planning with two types of demand for surgery: elective surgery and emergency surgery. Elective cases can be planned ahead and have a patient-related cost depending on the surgery date. Emergency cases arrive randomly and have to be performed on the day of arrival. The planning problem consists in assigning elective cases to different periods over a planning horizon in order to minimize the sum of elective patient related costs and overtime costs of operating rooms. A new stochastic mathematical programming model is first proposed. We then propose a Monte Carlo optimization method combining Monte Carlo simulation and Mixed Integer Programming. The solution of this method is proved to converge to a real optimum as the computation budget increases. Numerical results show that important gains can be realized by using a stochastic OR planning model.

State of art of optimization methods for assembly line design

The problem of optimal design of the assembly lines is considered. The paper is especially focused on the line balancing and resource planning step for the preliminary design stage. A survey of existing methods is given.

Supply planning under uncertainties in MRP environments: a state of the art

Inventory control in a supply chain is crucial for companies desiring to satisfy their customers demands as well as controlling costs. This paper examines specifically supply planning under uncertainties in MRP environments. Models from literature that deal with random demand or lead time uncertainties are described and commented. Promising research areas emerge from this survey. It appears that lead time uncertainty has been ignored in the past, in spite of their significant importance. In particular, an interesting topic concerns assembly systems with uncertain lead times, for which the main difficulty comes from the inter-dependence of components inventories. Another promising issue, which is also presented, relates to supply planning under simultaneously demand and lead time uncertainties, which is certainly of great interest for both the academic and industrial communities.

A model for supply planning under lead time uncertainty

The paper is focused on the search of the optimal values of the planned lead times for the MRP method under lead time uncertainty. The problem is to find the planned lead times, which minimize the expected backlogging and holding costs. The aim of the paper is to give a mathematical formulation of this single-level, multi-item, dynamic multi-period planning problem. For the case where lead time does not depend on the lot size and demand level is constant, an auxiliary Markov model is proposed. Some new formulations of optimal control policies are obtained using this Markov model.

The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management

This study aims at presenting the Ripple effect in supply chains. It develops different dimensions of the Ripple effect and summarises recent developments in the field of supply chain (SC) disruption management from a multi-disciplinary perspective. It structures and classifies existing research streams and applications areas of different quantitative methods to the Ripple effect analysis as well as identifying gaps in current research and delineating future research avenues. The analysis shows that different frameworks already exist implicitly for tackling the Ripple effect in the SC dynamics, control and disruption management domain. However, quantitative analysis tools are still rarely applied in praxis. We conclude that the Ripple effect can be the phenomenon that is able to consolidate research in SC disruption management and recovery similar to the bullwhip effect regarding demand and lead time fluctuations. This may build the agenda for future research on SC dynamics, control, continuity and disruption management, making supply chains more robust, adaptable and profitable.

MIP approach to balancing transfer lines with blocks of parallel operations

A novel line balancing problem is considered. It differs from assembly line balancing problems in that the operations of each workstation are partitioned into blocks of simultaneously executed (parallel) operations. The blocks of each workstation are executed sequentially. For the line design stage considered in this paper, the compatibility (inclusion and exclusion) constraints for grouping operations into blocks and workstations as well as precedence constraints are known. The goal is to minimize a weighted sum of the number of workstations and the number of blocks while achieving a desired cycle time and satisfying all the constraints. The developed exact and heuristic methods are based on a mixed-integer programming approach. Experimental results are reported.

Supply Chain Engineering

Supply Chain Engineering considers how modern production and operations management (POM) techniques can respond to the pressures of the competitive global marketplace by integrating all activities in the supply chain, adding flexibility to the system, and drastically reducing production cost. Several POM challenges are answered through a comprehensive analysis of concepts and models that assist the selection of outsourcing strategies and dynamic pricing policies. The ramifications of these topics are discussed from local to global perspectives. Supply Chain Engineering also presents • inventory control policies, • radio frequency identification (RFID) technologies, • flexible and re-configurable manufacturing systems, • real-time assignment and scheduling methods, • new warehousing techniques. In addition, a significant part of the book is devoted to: lean manufacturing, line balancing (assembly lines, U-lines, and bucket brigades), and dynamic facilities layout approaches. Explanations are given using basic examples and detailed algorithms, while discarding complex and unnecessary theoretical minutiae. Moreover, all the examples have been carefully selected with a view to eventual industrial application. Supply Chain Engineering is written for students and professors in industrial and systems engineering, management science, operations management, and business. It is also an informative reference for industrial managers looking to improve the efficiency and effectiveness of their production systems.

A special case of transfer lines balancing by graph approach

A balancing problem for paced production lines with workstations in series and blocks of parallel operations at the workstations is considered. Operations of each workstation are partitioned into blocks. All operations of the same block are performed simultaneously by one spindle head. All blocks of the same workstation are also executed simultaneously. The relations of the necessity of executing some operations at the same workstation, the possibility of combining the blocks at the same workstation as well as precedence constraints are given. The operation time of the workstation is the maximal value among operation times of its blocks. The line cycle time is the maximal workstation time. The problem is to choose blocks from a given set and allocate them to workstations in such a way that (i) all the operations are assigned, (ii) the above constraints are satisfied, (iii) a given cycle time is not exceeded, and (iv) the line cost is minimal. A method for solving the problem is based on its transformation to a constrained shortest path problem.

A heuristic approach for transfer lines balancing

The paper deals with optimal balancing transfer lines where the operations in each workstation are grouped into blocks. All operations of the same block are executed simultaneously by one spindle head. Spindle heads of the same workstation are activated sequentially. The workstation time is the sum of the processing times of its blocks. The problem is to find the best assignment of operations to blocks and assignment of blocks to workstations that leads to the minimal transfer line cost (a weighted sum of blocks and workstation numbers). The solution must provide a desired productivity rate (cycle time). It must also satisfy precedence and compatibility constraints. Two heuristic algorithms based on the COMSOAL technique are proposed. Results from computer testing are reported.

A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed.