Scheduling policies for multi-period services
•A new multi-period service problem is introduced and scheduling policies studied.•Integer programming formulations are proposed and analyzed.•A heuristic solution algorithm is presented.•Numerical results from extensive computational tests are presented and analyzed.•Computational experiments under...
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| Veröffentlicht in: | European journal of operational research Jg. 251; H. 3; S. 751 - 770 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article Verlag |
| Sprache: | Englisch |
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Amsterdam
Elsevier B.V
16.06.2016
Elsevier Sequoia S.A Elsevier |
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| ISSN: | 0377-2217, 1872-6860 |
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| Abstract | •A new multi-period service problem is introduced and scheduling policies studied.•Integer programming formulations are proposed and analyzed.•A heuristic solution algorithm is presented.•Numerical results from extensive computational tests are presented and analyzed.•Computational experiments underline the quality and effectiveness of the heuristic.
This paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times. |
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| AbstractList | •A new multi-period service problem is introduced and scheduling policies studied.•Integer programming formulations are proposed and analyzed.•A heuristic solution algorithm is presented.•Numerical results from extensive computational tests are presented and analyzed.•Computational experiments underline the quality and effectiveness of the heuristic.
This paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times. This paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times. Peer Reviewed This paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times. |
| Author | Kalcsics, Jörg Núñez-del-Toro, Cristina Fernández, Elena Nickel, Stefan |
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| SubjectTerms | 05 Combinatorics 90 Operations research, mathematical programming 90B Operations research and management science Classificació AMS Combinatorial analysis Combinatorial optimization Combinatòria Computational efficiency Customer satisfaction Customer services Customers Demand Heuristic Heuristics Integer programming Investigació operativa Linear programming Matemàtica discreta Matemàtiques i estadística Mathematical models Multi-period problems Operations research Operators Optimització Policies Scheduling Scheduling algorithms Service scheduling Studies Àrees temàtiques de la UPC |
| Title | Scheduling policies for multi-period services |
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