scholarly journals A Simulation-Based Optimization Method for Warehouse Worker Assignment

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 326
Author(s):  
Odkhishig Ganbold ◽  
Kaustav Kundu ◽  
Haobin Li ◽  
Wei Zhang
Keyword(s):  
Discrete Event ◽  
Real Data ◽  
Optimization Method ◽  
Service Level ◽  
Neighborhood Search ◽  
Support Tool ◽  
Worker Allocation ◽  
Time Problem ◽  
Simulation Based ◽  
Simulation Based Optimization

The general assignment problem is a classical NP-hard (non-deterministic polynomial-time) problem. In a warehouse, the constraints on the equipment and the characteristics of consecutive processes make it even more complicated. To overcome the difficulty in calculating the benefit of an assignment and in finding the optimal assignment plan, a simulation-based optimization method is introduced. We first built a simulation model of the warehouse with the object-oriented discrete-event simulation (O2DES) framework, and then implemented a random neighborhood search method utilizing the simulation output. With this method, the throughput and service level of the warehouse can be improved, while keeping the number of workers constant. Numerical results with real data demonstrate the reduction of discrepancy between inbound and outbound service level performance. With a less than 10% reduction in inbound service level, we can achieve an over 30% increase in outbound service level. The proposed decision support tool assists the warehouse manager in dealing with warehouse worker allocation problem under conditions of random daily workload.

Simulation-Based Optimization of Electricity Demand Response for Sustainable Manufacturing Systems

2014 ◽  
Author(s):  
Leah Cuyler ◽  
Zeyi Sun ◽  
Lin Li
Keyword(s):  
Demand Response ◽  
Manufacturing Systems ◽  
Manufacturing Sector ◽  
Sustainable Manufacturing ◽  
Optimization Method ◽  
Electricity Demand ◽  
System Throughput ◽  
Commercial Building ◽  
Simulation Based ◽  
Simulation Based Optimization

Electricity demand response is considered a promising tool to balance the electricity demand and supply during peak periods. It can effectively reduce the cost of building and operating those peaking power generators that are only run a few hundred hours per year to satisfy the peak demand. The research on the electricity demand response implementation for residential and commercial building sectors has been very mature. Recently, it has also been extended to the manufacturing sector. In this paper, a simulation-based optimization method is developed to identify the optimal demand response decisions for the typical manufacturing systems with multiple machines and buffers. Different objectives, i.e. minimizing the power consumption under the constraint of system throughput, and maximize the overall earnings considering the tradeoff between power demand reduction and potential production loss, are considered. Different energy control decisions are analyzed and compared regarding the potential influence on the throughput of manufacturing system due to the different control actions adopted by throughput bottleneck machine.

Solder parameter sensitivity for CSP life-time prediction using simulation-based optimization method

2002 ◽  
Vol 25 (4) ◽  
pp. 318-325 ◽  
Author(s):  
B. Vandevelde ◽  
E. Beyne ◽  
K.G.Q. Zhang ◽  
J.F.J.M. Caers ◽  
D. Vandepitte ◽  
...  
Keyword(s):  
Life Time ◽  
Optimization Method ◽  
Parameter Sensitivity ◽  
Time Prediction ◽  
Simulation Based ◽  
Simulation Based Optimization

Integrating Resource Management in Service Network Design for Bike-Sharing Systems

2020 ◽  
Vol 54 (5) ◽  
pp. 1251-1271
Author(s):  
Bruno Albert Neumann-Saavedra ◽  
Teodor Gabriel Crainic ◽  
Bernard Gendron ◽  
Dirk Christian Mattfeld ◽  
Michael Römer
Keyword(s):  
Resource Management ◽  
Network Design ◽  
Discrete Event ◽  
Service Level ◽  
Neighborhood Search ◽  
Mobility Patterns ◽  
Service Network ◽  
Service Network Design ◽  
Bike Sharing ◽  
Problem Instances

Station-based bike-sharing systems rely on bike redistribution to provide users with an adequate service level. We propose a novel formulation of service network design that coordinates redistribution decisions in space and time to plan regular master tours. This formulation explicitly integrates resource-management decisions by considering a limited redistribution budget to acquire and operate vehicles, as well as an accurate time representation of pickups and deliveries of bikes at stations. We propose a matheuristic relying on a neighborhood search scheme to find solutions of good quality for real-world-sized problem instances in reasonable time. To produce starting solutions, we propose a construction heuristic decomposing the daytime redistribution process into three sequential phases: determine pickups and deliveries, link pickups and deliveries into transport requests, and assign transport requests to master tours. We evaluate the operational performance of master tours with a discrete-event simulation approach. We show that master tours improve the level of service in bike-sharing systems with high and regular mobility patterns, for example, commuting activities.

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