Abstract:Product allocation is one of the most important duties in warehousing operations. Based on the time and the number of products to put away and retrieve, storage allocation can directly affect the efficiency of a warehouse in terms of both response and operation time. Traditionally, the product storage allocation is done based on the less distance of shipment but focusing on distance may decrease the efficiency of a warehouse in terms of efficient utilization of resources such as warehouse inbound shipping flee… Show more
“…The results highlight the possibility to minimize the energy consumption, ensuring low cycle times. A further approach with the target of reducing the idle time of forklifts is proposed by Ghalehkhondabi and Masel [19]. The authors propose a storage space allocation model that considers the availability of forklifts.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In particular, (17) initializes the battery capacity in forklifts in the jobs allocated at the beginning of the planning horizon, whilst (18) calculates the residual battery capacity by first-order state transition between subsequent activities. Constraint (19) updates the residual battery capacity at the beginning of activity i, taking into account the eventual replacement with a fully charged battery. Constraint (20) guarantees that the capacity of the battery in any forklift is enough to complete job i, whilst (21) guarantees that the capacity of the battery in any forklift at the end of the final setup is not lower than the required final state.…”
Section: Second-step Optimizationmentioning
confidence: 99%
“…Summing up, the second-step optimization problem (12)-(40) is a non-linear integer program, since cross-product terms z mn i β m i , s m i z mn i , r m i z mn i , and δ mt i z mn i are present in (19) and (33), (23), (24) and (25), and (34), respectively. The resolution of (12)-(40) allows the determination of the optimal job scheduling s m i , c m i , the battery replacement strategies z mn i , and the charging station energy scheduling ρ mt i .…”
Section: Second-step Optimizationmentioning
confidence: 99%
“…Job index k [ 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30 ] Job priority p k [ 30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,…”
In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses’ energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously.
“…The results highlight the possibility to minimize the energy consumption, ensuring low cycle times. A further approach with the target of reducing the idle time of forklifts is proposed by Ghalehkhondabi and Masel [19]. The authors propose a storage space allocation model that considers the availability of forklifts.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In particular, (17) initializes the battery capacity in forklifts in the jobs allocated at the beginning of the planning horizon, whilst (18) calculates the residual battery capacity by first-order state transition between subsequent activities. Constraint (19) updates the residual battery capacity at the beginning of activity i, taking into account the eventual replacement with a fully charged battery. Constraint (20) guarantees that the capacity of the battery in any forklift is enough to complete job i, whilst (21) guarantees that the capacity of the battery in any forklift at the end of the final setup is not lower than the required final state.…”
Section: Second-step Optimizationmentioning
confidence: 99%
“…Summing up, the second-step optimization problem (12)-(40) is a non-linear integer program, since cross-product terms z mn i β m i , s m i z mn i , r m i z mn i , and δ mt i z mn i are present in (19) and (33), (23), (24) and (25), and (34), respectively. The resolution of (12)-(40) allows the determination of the optimal job scheduling s m i , c m i , the battery replacement strategies z mn i , and the charging station energy scheduling ρ mt i .…”
Section: Second-step Optimizationmentioning
confidence: 99%
“…Job index k [ 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30 ] Job priority p k [ 30,29,28,27,26,25,24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,…”
In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses’ energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously.
“…Reducing the cost of warehouse operations is one of the main tasks in the designing of warehouses and the selection of material handling equipment and storage systems. Solutions of this task can be found by optimizing space utilization (e.g., Derhami et al, 2017), reducing the total travelled distance by the fork-lifts (Ghalehkhondabi and Masel, 2018), using automated storage and retrieval systems (AS/RSs), autonomous vehicle storage and retrieval systems (AVS/RSs) (Heragu et al, 2011) and Shuttle-Based Storage and Retrieval Systems (SBS/Rs) (Lerher et al, 2017) for increasing the throughput of warehouse operations.…”
Pallet flow rack are widely used in intralogistics to maximize warehouse capacity and to reduce the travel by fork-lifts. However, the use of pallet flow racks is associated with increased danger due to the use of gravity conveyors in their design. For this purpose, the gravity conveyors of pallet flow rack have a two safety elements – brake rollers and a stopping mechanism with pallet separator, which are working as a system. Brake rollers limit the speed of pallets, while the stopping mechanism allows exuding a pressure on the unloading pallet from the following behind it. A pallet should have such a speed, controlled by the brake rollers, so that it could be stopped by a stopping mechanism without damaging it. Based on the Cox impact theory, an original method for determining the allowable speed of a pallet in a pallet flow rack is proposed. The method ensures safe operation of the stopping mechanism with pallet separator and takes into account the mechanical properties and design parameters of the pallet separator stopper. A calculation example is provided for the most commonly used types of pallets – Euro pallet (1200 mm × 800 mm) and Industrial pallet (1200 mm × 1000 mm). The obtained results agree well with the pallet speed range of 0.2 to 0.3 m/s recommended by the manufacturers of pallet flow racks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.