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Medical devices cycle 

Medical devices cycle 

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Conference Paper
Full-text available
The operating theater scheduling problem is one of the main hospital sector issues of today’s world. Indeed, numerous papers dealing with this subject may be found in the literature. However, the synchronization between the pharmacy (providing the surgical devices and medicines) and the operating theater is rarely studied. Nevertheless, the importa...

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Context 1
... sterilization service of the pharmacy is responsible for the washing, the ster- ilization and the repackaging of the medical devices into boxes (we simply denote them "boxes" in the remainder of the paper). When a surgical procedure occurs, the corresponding box follows a precise cycle (summarized in Fig. 1). Before the surgical procedure starts, the appropriate box (or boxes) is (are) sent from the sterilization service to the operating theater with a vehicle (automated or not) or sometimes directly via a human agent. The box is brought to the appropriate operating room to be used during the procedure (it can be stored in the service ...
Context 2
... respect it, which is easily identifiable on a graphic representation, an example of a four-surgical operation planing is presented on Fig. 2. This example presents the time repartition of the four surgical operations, the black strip represent the time during which the corresponding box will be unavailable, it corresponds to a complete box cycle (Fig. 1). In this condition, the best planning is the one with the lowest evaluation (lower amount of boxes needed to be ...
Context 3
... are updated at each step if needed. The neighborhood of a particle j is a set composed of every other particles i which distance d k i,j is lesser than D, the distance between two particles is given by Eq. (13). Here the Euclidian distance is used in order to create neighborhood composed of slightly similar solutions, that is to say solutions with some small time offsets. ...
Context 4
... sterilization service of the pharmacy is responsible for the washing, the ster- ilization and the repackaging of the medical devices into boxes (we simply denote them "boxes" in the remainder of the paper). When a surgical procedure occurs, the corresponding box follows a precise cycle (summarized in Fig. 1). Before the surgical procedure starts, the appropriate box (or boxes) is (are) sent from the sterilization service to the operating theater with a vehicle (automated or not) or sometimes directly via a human agent. The box is brought to the appropriate operating room to be used during the procedure (it can be stored in the service before the operation starts if necessary). When the surgical procedure is over, the medical devices are pre-disinfected by immersing them into a disinfectant liquid during twenty minutes (average duration). Then the instruments are repacked in the right box and stored in a common dedicated zone before being sent back to the sterilization service of the pharmacy. When the boxes are received by the service, they follow several steps to be sterilized. First the medical devices are divided among automatic washers to be cleaned. When the washing program is over, the materials must be repacked in the corresponding boxes. This opera- tion may be long or less and complex depending on the number of instruments (which might exceed one hundred) and the complexity of the placement in the box. The repacked boxes are then stored in a dedicated buffering zone. When the adequate number of boxes are stored, they are put into autoclaves (steriliza- tion machines) to be sterilized. This process lasts more than an hour. When it is over, the boxes are stored while their temperature drops. After this step, the sterilization process is over and the boxes are available. They may be sent to the operation theater to continue the cycle when needed. It is important to notice that this cycle may be interrupted during precise moments (before/after wash- ing or before/after sterilizating) but under no circumstances during the surgical ...
Context 5
... are a lot of papers that compare the operating theater to an hybrid flow-shop [11,14,15,23]. These studies assimilate the patients to jobs and the operating theater steps to machines. In this work, we concentrate on surgical devices. Consequently, we assimilate surgical procedures to jobs and boxes to machines. In this context, according to the nomenclature, the problem must be compared to a "RI/ prec,pmtn/Boxes utilization minimization" problem. α 1 = R means that the operations are parallel and unrelated. Despite the fact that the machines represent the same type of box, the time needed for a job depends on other parameters (the patient, the surgeon...). α 2 = I means that the number of machines (or boxes) is fixed. β = prec,pmtn prec means 'precedence'. We separate each job into two sub-jobs. The first sub- job represents the operating theater and transportation part and the second one represents the sterilization service part. Hence we add a precedence constraint between these two sub-jobs (operating theater first then sterilization). pmtn means 'preemption'. As said before, the sterilization sub-jobs may be pre- empted. γ = "Boxes utilization minimization". There is no pre-existing parameter which correctly represents our scheduling problem performance criterion. Indeed, we try to minimize the number of machines (boxes) which will be used and this kind of criterion is rarely considered in the literature. To model the operating theater scheduling problem considering the steril- ization step, each prescribed surgical procedure is represented by a job j the duration of which corresponds to the time needed to perform a complete cycle of the corresponding box (see Sect. 2.2). The job starts simultaneously with the corresponding surgical procedure. Therefore two distinct surgical procedures can share a same box only if the corresponding jobs do not overlap. It is then pos- sible to represent a complete planning for a given procedure type (sharing the same type of medical devices). This planning may be evaluated by calculating the number of boxes needed to respect it, which is easily identifiable on a graphic representation, an example of a four-surgical operation planing is presented on Fig. 2. This example presents the time repartition of the four surgical operations, the black strip represent the time during which the corresponding box will be unavailable, it corresponds to a complete box cycle (Fig. 1). In this condition, the best planning is the one with the lowest evaluation (lower amount of boxes needed to be ...
Context 6
... j and G j represent the position vectors of the best solutions found by the particle j and by the particles in its neighborhood respectively. They are updated at each step if needed. The neighborhood of a particle j is a set composed of every other particles i which distance d k i,j is lesser than D, the distance between two particles is given by Eq. (13). Here the Euclidian distance is used in order to create neighborhood composed of slightly similar solutions, that is to say solutions with some small time offsets. Moreover, it is important to note that here the distance between two solutions must be expressed in time units (commonly hours). ω represents the system global inertia. A high inertia value implies a better solution space exploration at the expense of the convergence speed. φ 1 and φ 2 represent the personal memory factor and the common knowledge factor respectively. If φ 1 is set to a high value, each particle will be more attracted by its own best already visited position L j . If φ 2 is set to a high value, each particle will be more attracted by the best already visited position among every visited positions of every particles G j ...

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... Researchers are starting to incorporate the SPD. Beroule et al. [76] employed particle swarm optimization to determine a schedule that minimized the number of instrument boxes needed to complete all surgeries for a given week. Considering box usage as the sole objective in OR scheduling is not necessarily realistic. ...
... Linear Programming [12,28,40,77,88,160,172,179,202,222] Integer Programming [10,19,33,55,88,93,101,111,118,119,126,151,154,165,166,176,183,191,196,204,205,208,216,236,251,261] Mixed Integer Programming [11, 14, 15, 18, 21-25, 27, 31, 32, 35, 36, 38, 41, 42, 45-47, 49-53, 58-60, 62, 63, 66, 67, 70, 81, 83, 85, 86, 91, 94, 96, 97, 106, 110, 112, 115, 116, 123, 125, 129-131, 135-138, 142, 143, 145, 148-150, 157-161, 164, 169, 175, 178, 180, 181, 184, 186-188, 192, 197-201, 206, 207, 210, 217-221, 227, 229-234, 237-239, 241-249, 252, 254, 257, 259, 260, 262, 264] Integer Linear Programming [13,54,108,146,162,168,170,193,194,213,224] Mixed Integer Linear Programming [16, 17, 26, 30, 34, 39, 43, 44, 56, 57, 61, 64, 74, 76, 79, 93, 95, 97-100, 102, 103, 109, 117, 121, 122, 124, 127, 128, 139, 140, 144, 152, 167, 171, 174, 177, 182, 185, 189, 209, 223, 228, 235, 240] Constraint Programming [114,120,126,152,167,204,237,254] Goal Programming [28,82,83,120,162,187,213,230] Other [32,63,65,71,72,88,93,104,138,215] Heuristic Simulated Annealing [52,68,81,94,122,123,125,179,192,195,219,221,228] Genetic Algorithm [25,35,37,42,51,55,63,75,109,117,119,122,129,152,158,162,169,170,192,212,223,229,235,243,264] Particle Swarm Optimization [25,63,76,238,242] Other [15, 20, 32, 35, 36, 39, 40, 42, 43, 47, 49, 50, 55, 58, 59, 73, 75, 77, 81, 88, 98, 102, 103, 110, 112, 115, 118, 125, 137, 139-142, 145, 146, 148, 151, 155-158, 172, 174, 178, 179, 182, 188, 192, 194, 202, 205, 206, 208, 210, 216, 219, 223, 224, 227-229, 232, 238-240, 242, 244-247, 252, 258, 262] Algorithm [12, 13, 16, 17, 22, 33, 34, 36, 37, 39, 42-44, 46, 47, 49, 50, 53, 67, 69, 70, 74, 78, 81, 88, 90, 93, 94, 96, 99-101, 105-108, 114, 115, 126, 130, 132, 134, 135, 138, 141, 143, 150-152, 154, 156, 157, 172, 176, 177, 179-182, 184, 186, 187, 189-191, 196, 200, 204-207, 210, 215, 218-220, 228, 231, 233, 234, 241, 248, 249, 259-262] Sample Average Approximation [26,27,39,46,52,100,110,118,135,136,138,160,166,175,178,228,229,232,239,257] Column Generation [50,59,73,126,139,157,191,199,239,257] Though still relatively scarce, researchers have started to use simulation optimization. Zhang and Xie [260] utilized it to determine optimal surgeon arrival times for an OR suite in China. ...
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