scholarly journals Workforce Scheduling with Order-Picking Assignments in Distribution Facilities

2021 ◽  
Author(s):  
Arpan Rijal ◽  
Marco Bijvank ◽  
Asvin Goel ◽  
René de Koster
Keyword(s):  
Time Windows ◽  
Real Life ◽  
Labor Cost ◽  
Order Picking ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Workforce Scheduling ◽  
Solution Approach ◽  
Business Application ◽  
End Times

Scheduling the availability of order pickers is crucial for effective operations in a distribution facility with manual order pickers. When order-picking activities can only be performed in specific time windows, it is essential to jointly solve the order picker shift scheduling problem and the order picker planning problem of assigning and sequencing individual orders to order pickers. This requires decisions regarding the number of order pickers to schedule, shift start and end times, break times, as well as the assignment and timing of order-picking activities. We call this the order picker scheduling problem and present two formulations. A branch-and-price algorithm and a metaheuristic are developed to solve the problem. Numerical experiments illustrate that the metaheuristic finds near-optimal solutions at 80% shorter computation times. A case study at the largest supermarket chain in The Netherlands shows the applicability of the solution approach in a real-life business application. In particular, different shift structures are analyzed, and it is concluded that the retailer can increase the minimum compensated duration for employed workers from six hours to seven or eight hours while reducing the average labor cost with up to 5% savings when a 15-minute flexibility is implemented in the scheduling of break times.

scholarly journals Solving the Torpedo Scheduling Problem

2019 ◽  
Vol 66 ◽  
pp. 1-32
Author(s):  
Martin Josef Geiger ◽  
Lucas Kletzander ◽  
Nysret Musliu
Keyword(s):  
Material Flow ◽  
Simulated Annealing Algorithm ◽  
Steel Production ◽  
Experimental Investigations ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Solution Approach ◽  
Annealing Algorithm ◽  
Problem Instances ◽  
Continuous Material

The article presents a solution approach for the Torpedo Scheduling Problem, an operational planning problem found in steel production. The problem consists of the integrated scheduling and routing of torpedo cars, i. e. steel transporting vehicles, from a blast furnace to steel converters. In the continuous metallurgic transformation of iron into steel, the discrete transportation step of molten iron must be planned with considerable care in order to ensure a continuous material flow. The problem is solved by a Simulated Annealing algorithm, coupled with an approach of reducing the set of feasible material assignments. The latter is based on logical reductions and lower bound calculations on the number of torpedo cars. Experimental investigations are performed on a larger number of problem instances, which stem from the 2016 implementation challenge of the Association of Constraint Programming (ACP). Our approach was ranked first (joint first place) in the 2016 ACP challenge and found optimal solutions for all used instances in this challenge.

scholarly journals Production planning and scheduling problem of continuous parallel lines with demand uncertainty and different production capacities

2020 ◽  
Vol 7 (6) ◽  
pp. 761-774
Author(s):  
Kailash Changdeorao Bhosale ◽  
Padmakar Jagannath Pawar
Keyword(s):  
Production Planning ◽  
Demand Uncertainty ◽  
Clustering Algorithm ◽  
Real Life ◽  
Initial Population ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling

Abstract Production planning and scheduling problems are highly interdependent as scheduling provides optimum allocation of resources and planning is an optimum utilization of these allocated resources to serve multiple customers. Researchers have solved production planning and scheduling problems by the sequential method. But, in this case, the solution obtained by the production planning problem may not be feasible for scheduling method. Hence, production planning and scheduling problems must be solved simultaneously. Therefore, in this work, a mathematical model is developed to integrate production planning and scheduling problems. The solution to this integrated planning and scheduling problem is attempted by using a discrete artificial bee colony (DABC) algorithm. To speed up the DABC algorithm, a k-means clustering algorithm is used in the initial population generation phase. This k-means clustering algorithm will help to converge the algorithm in lesser time. A real-life case study of a soap manufacturing industry is presented to demonstrate the effectiveness of the proposed approach. An objective function to minimize overall cost, which comprises the processing cost, material cost, utility cost, and changeover cost, is considered. The results obtained by using DABC algorithm are compared with those obtained by CPLEX software. There is a saving of ₹2 23 324 for weeks 1–4 in overall cost compared with the results obtained by using CPLEX software.

REAL-LIFE VEHICLE ROUTING WITH TIME WINDOWS FOR VISUAL ATTRACTIVENESS AND OPERATIONAL ROBUSTNESS

2012 ◽  
Vol 29 (04) ◽  
pp. 1250017 ◽  
Author(s):  
B. L. HOLLIS ◽  
P. J. GREEN
Keyword(s):  
Vehicle Routing ◽  
Search Algorithm ◽  
Time Windows ◽  
Real Life ◽  
Second Phase ◽  
Two Phase ◽  
Guided Local Search ◽  
Solution Approach ◽  
Robust Solutions ◽  
Phase Solution

This paper describes an algorithm for producing visually attractive and operationally robust solutions to a real-life vehicle routing problem with time windows. Visually attractive and operationally robust solutions are usually synonymous with compact, nonoverlapping routes with little or no intra-route cross over. The visual attractiveness of routes, for practical routing applications, is often of paramount importance. We present a two phase solution approach. The first phase is inspired by the sequential insertion algorithm of Solomon (1987) and includes a range of novel enhancements to ensure visually attractive solutions are produced in the face of a range of nonstandard real-life constraints: A constrained and heterogeneous vehicle fleet; tight time windows and banned delivery windows; multiple route capacity measures; driver breaks; minimum route volumes; vehicle-location compatibility rules; nonreturn to base routes; peak hour traveling times; vehicle type dependent service times; and replenishment back at the depot. The second phase is based on the guided local search algorithm of Kilby et al. (1999). It uses an augmented objective function designed to seek solutions which strike a balance between minimizing traditional cost measures, whilst maximizing the visual attractiveness of the solution. Our two phase solution approach is particularly adept at producing solutions that both aggressively minimize the total number of routes, a feature that we believe has been missing in algorithms presented in equivalent literature, as well as minimizing traditional cost measures whilst delivering a very high degree of visual attractiveness. The algorithm presented has been successfully implemented and deployed for the real-life, daily beverage distribution problem of Schweppes Australia Pty. Ltd. for a range of capital cities throughout Australia.

scholarly journals The operational flight and multi-crew scheduling problem

2005 ◽  
Vol 15 (1) ◽  
pp. 25-48 ◽  
Author(s):  
Mirela Stojkovic ◽  
François Soumis
Keyword(s):  
Network Flow ◽  
Time Windows ◽  
Optimal Solution ◽  
Crew Scheduling ◽  
Scheduling Problem ◽  
Sequential Approach ◽  
Solution Approach ◽  
Departure Time ◽  
New Type ◽  
Crew Scheduling Problem

This paper introduces a new kind of operational multi-crew scheduling problem which consists in simultaneously modifying, as necessary, the existing flight departure times and planned individual work days (duties) for the set of crew members, while respecting predefined aircraft itineraries. The splitting of a planned crew is allowed during a day of operations, where it is more important to cover a flight than to keep planned crew members together. The objective is to cover a maximum number of flights from a day of operations while minimizing changes in both the flight schedule and the next-day planned duties for the considered crew members. A new type of the same flight departure time constraints is introduced. They ensure that a flight which belongs to several personalized duties, where the number of duties is equal to the number of crew members assigned to the flight, will have the same departure time in each of these duties. Two variants of the problem are considered. The first variant allows covering of flights by less than the planned number of crew members, while the second one requires covering of flights by a complete crew. The problem is mathematically formulated as an integer nonlinear multi-commodity network flow model with time windows and supplementary constraints. The optimal solution approach is based on Dantzig-Wolfe decomposition/column generation embedded into a branch-and-bound scheme. The resulting computational times on commercial-size problems are very good. Our new simultaneous approach produces solutions whose quality is far better than that of the traditional sequential approach where the flight schedule has been changed first and then input as a fixed data to the crew scheduling problem.

scholarly journals Modelling of integrated scheduling problem of capacitated equipment systems with a multi-lane road network

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251875
Author(s):  
Di Luan ◽  
Mingjing Zhao ◽  
Qianru Zhao ◽  
Nan Wang
Keyword(s):  
Optimization Algorithms ◽  
Real Life ◽  
Bilevel Optimization ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Mixed Integer ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Integrated Scheduling ◽  
Container Handling

The coordination of different container-handling equipment is an important method for improving the overall efficiency of automated container terminals. In the real terminal, we should consider many real-life issues, such as the equipment capacity, the equipment collision, changing lanes in the multi-lane road, and choosing one of container-handling lanes for each container. This paper proposes the integrated scheduling problem of three container-handling equipment with the capacity constraint and the dual-cycle strategy, for simultaneously solving the equipment scheduling problem, the assignment problem of the container-handling lane and the conflict-free route planning problem of automated guided vehicles (AGVs). With the objective of minimizing the ship’s berth time, we propose a mixed-integer programming model based on the space-time network representation method and two bilevel optimization algorithms based on conflict resolution rules. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model and two bilevel optimization algorithms.

scholarly journals Analysis of Dynamic Changes in Cognitive Workload During Cardiac Surgery Perfusionists′ Interactions With the Cardiopulmonary Bypass Pump

2020 ◽  
pp. 001872082097629
Author(s):  
Lauren R. Kennedy-Metz ◽  
Roger D. Dias ◽  
Rithy Srey ◽  
Geoffrey C. Rance ◽  
Heather M. Conboy ◽  
...  
Keyword(s):  
Cardiac Surgery ◽  
Cardiopulmonary Bypass ◽  
Heart Surgery ◽  
Time Windows ◽  
Open Heart Surgery ◽  
Real Life ◽  
Skin Incision ◽  
Cognitive Workload ◽  
Dynamic Changes ◽  
Pump Operation

Objective This novel preliminary study sought to capture dynamic changes in heart rate variability (HRV) as a proxy for cognitive workload among perfusionists while operating the cardiopulmonary bypass (CPB) pump during real-life cardiac surgery. Background Estimations of operators’ cognitive workload states in naturalistic settings have been derived using noninvasive psychophysiological measures. Effective CPB pump operation by perfusionists is critical in maintaining the patient’s homeostasis during open-heart surgery. Investigation into dynamic cognitive workload fluctuations, and their relationship with performance, is lacking in the literature. Method HRV and self-reported cognitive workload were collected from three Board-certified cardiac perfusionists ( N = 23 cases). Five HRV components were analyzed in consecutive nonoverlapping 1-min windows from skin incision through sternal closure. Cases were annotated according to predetermined phases: prebypass, three phases during bypass, and postbypass. Values from all 1min time windows within each phase were averaged. Results Cognitive workload was at its highest during the time between initiating bypass and clamping the aorta (preclamp phase during bypass), and decreased over the course of the bypass period. Conclusion We identified dynamic, temporal fluctuations in HRV among perfusionists during cardiac surgery corresponding to subjective reports of cognitive workload. Not only does cognitive workload differ for perfusionists during bypass compared with pre- and postbypass phases, but differences in HRV were also detected within the three bypass phases. Application These preliminary findings suggest the preclamp phase of CPB pump interaction corresponds to higher cognitive workload, which may point to an area warranting further exploration using passive measurement.

scholarly journals Robust neutrosophic programming approach for solving intuitionistic fuzzy multiobjective optimization problems

2021 ◽  
Author(s):  
Firoz Ahmad
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Practical Implication ◽  
Real Life ◽  
Future Research ◽  
Programming Approach ◽  
Solution Approach ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiobjective Optimization Problems

AbstractThis study presents the modeling of the multiobjective optimization problem in an intuitionistic fuzzy environment. The uncertain parameters are depicted as intuitionistic fuzzy numbers, and the crisp version is obtained using the ranking function method. Also, we have developed a novel interactive neutrosophic programming approach to solve multiobjective optimization problems. The proposed method involves neutral thoughts while making decisions. Furthermore, various sorts of membership functions are also depicted for the marginal evaluation of each objective simultaneously. The different numerical examples are presented to show the performances of the proposed solution approach. A case study of the cloud computing pricing problem is also addressed to reveal the real-life applications. The practical implication of the current study is also discussed efficiently. Finally, conclusions and future research scope are suggested based on the proposed work.

scholarly journals Decision support framework for the regional facility location and development planning problem

2021 ◽  
Author(s):  
David Kik ◽  
Matthias Gerhard Wichmann ◽  
Thomas Stefan Spengler
Keyword(s):  
Decision Support ◽  
Facility Location ◽  
Future Orientation ◽  
Real Life ◽  
Development Planning ◽  
Major Influence ◽  
Location Decisions ◽  
Planning Problem ◽  
Location Factor ◽  
Decision Support Framework

AbstractLocation choice is a crucial planning task with major influence on a company’s future orientation and competitiveness. It is quite complex, since multiple location factors are usually of decision-relevance, incomparable, and sometimes conflictual. Further, ongoing urbanization is associated with locational dynamics posing major challenges for the regional location management of companies and municipalities. For example, respecting urban space as location factor, a scarcity growing over time leads to different assessment and requirements on a company’s behalf. For both companies and municipalities, there is a need for location development which implies an active change of location factor characteristics. Accordingly, considering locational dynamics is vital, as they may be decisive in the location decision-making. Although certain dynamics are considered within conventional Facility Location Problem (FLP) approaches, a systematic consideration of active location development is missing so far. Consequently, they may propagate long-term unfavorable location decisions, as major potentials associated with company-driven and municipal development measures are neglected. Therefore, this paper introduces a comprehensive decision support framework for the Regional Facility Location and Development planning Problem (RFLDP). It provides an operationalization of development measures, and thus anticipates dynamic adaptations to the environment. An established multi-criteria approach is extended to this new application. A complementary guideline ensures its meaningful applicability by practitioners. Based on a real-life case study, the decision support framework’s strength for practical application is demonstrated. Here, major advantages over conventional FLP approaches are highlighted. It is shown that the proposed methodology results in alternative location decisions which are structurally superior.

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