• 품질경영학회지
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• 제18권2호
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• pp.81-92
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• 1990

This paper considers a scheduling of a set of jobs on single and multiple processors, when all jobs have a common due date and earliness and lateness are penalized at different cost rates. The objective is to determine the optimal value of a common due date and an optimal scheduling to minimize a total penalty function. It is also shown that a schedule having minimum weighted completion time variances must be V-shaped. For identical processors, a polynomial scheduling algorithm with the secondary objectives of minimizing makespan and machine occupancy is developed and a numerical example is presented.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.64-66
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• 2004

In general, the algorithms for production scheduling are developed with special objective under the special restrictions. Therefore, there is no common algorithm for APS system applied to various kind of production circumstances. The scheduling algorithm for APS system has to solve any problem that comes from any conditions of product kind, process, resource, machine, special rule for scheduling, and so forth. In addition, the algorithm finds solutions quickly because the need for real time based reschedule comes out often. In this paper, I am going to develop a scheduling algorithm using heuristic and genetic algorithm for APS system applied to various kind of production circumstances quickly and flexibly. The developed APS system with the algorithm will be introduced in this paper, also.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.615-619
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• 2004

This paper considers a variation of customer order scheduling problems. The variation is the case where machine-job assignment is fixed, and the objective is to minimize the sum of the completion times of the batches. In customer order scheduling problems, jobs are dispatched in batches. While a machine can process only one job at a time, multiple machines can simultaneously process jobs in a batch. We first establish a couple of lower bounds. Then, we develop a dynamic programming (DP) algorithm that runs in exponential time on the number of batches when there exist two machines. For the same problem with arbitrary number of machines, we present two simple heuristics, which use simple scheduling rules such as shortest batch first and shortest makespan batch first rules. Finally, we empirically evaluate the heuristics.

• 한국경영과학회지
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• 제19권3호
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• pp.139-149
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• 1994

In many project-oriented production systems, e. g., shipyards or large-scale steel products manufacturing, resource loading by an activity is flexible, and the activity duration is a function of resource allocation. For example, if one doubles the size of the crew assigned to perform an activity, it may be feasible to complete the activity in half the duration. Such flexibility has been modeled by Weglarz [13] and by Leachman, Dincerler, and Kim [7[ in extended formulations of the resource-constrained poject scheduling problem. This paper presents a new algorithmic approach to the problem that combines the ideas proposed by the aforementioned authors. The method we propose involves a two-step approach : (1) solve the resource-constrained scheduling problem using a heuristic, and (2) using this schedule as an initial feasible solution, find improved resource allocations by solving a linear programming model. We provide computational results indicating the superiority of this approach to previous methodology for the resource-constrained scheduling problem. Extensions to the model to admit overlap relationship of the activities also are presented.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• 경영과학
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• 제21권1호
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• pp.39-55
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• 2004

Efficient crew scheduling for cockpit crew is important in airline industry due to operational safety and cost associated with the flight duty time. Because of complexity of regulations imposed to the cockpit crew. it is complicated to generate an efficient schedule. Schedule of cockpit crew can be generated through two steps; selecting of flight patterns. and scheduling of them to the specific time horizon. Heuristic method is developed and applied with massive data in a limited time of computation. A set of flight patterns is selected from all possible flight patterns. which are generated by composing the flight leg based on regulations. by using the set partitioning problem with objective function of oversea stay cost. The selected set of flight patterns found at the first step is allocated to 4 week crew schedule to minimize the variance of total fight time assigned to each crew. The crew schedules obtained are evaluated and compared with the ones currently used in one of major airline company.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.613-616
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• 2000

This paper considers the problem of subway crew scheduling. Crew scheduling is concerned with finding a minimum number of assignments of crews to a given timetable satisfying various restrictions. Traditionally, crew scheduling problem has been formulated as a set covering or set partitioning problem possessing exponentially many variables, but even the LP relaxation of the problem is hard to solve due to the exponential number of variables. In this paper, we propose two basic techniques that solve the problem in a reasonable time, though the optimality of the solution is not guaranteed. To reduce the number of variables, we adopt column-generation technique. We could develop an algorithm that solves column-generation problem in polynomial time. In addition, the integrality of the solution is accomplished by variable-fixing technique. Computational results show column-generation makes the problem of treatable size, and variable fixing enables us to solve LP relaxation in shorter time without a considerable increase in the optimal value. Finally, we were able to obtain an integer optimal solution of a real instance within a reasonable time.

• 한국항공운항학회지
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• 제25권3호
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• pp.44-50
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• 2017

This paper proposes arrival scheduling and advisory generation algorithms which can be used in the terminal airspace with Point-Merge procedures. The proposed scheduling algorithm consists of two steps. In the first step, the algorithm computes aircraft schedules at the entrance of the Point-Merge sequencing legs based on First-Come First-Served(FCFS) strategy. Then, in the second step, optimal sequence and schedules of all aircraft at the runway are computed using Multi-Objective Dynamic Programming(MODP) method. Finally, the advisories that have to be provided to the air traffic controllers are generated. To demonstrate the proposed algorithms, the simulation was conducted based on Jeju International Airport environments.

• 산업공학
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• 제25권3호
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• pp.357-364
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• 2012

This paper considers a unrelated parallel machine scheduling problem with ready times, due times and sequence and machine-dependent setup times. The objective of this problem is to determine the allocation of jobs and the scheduling of machines to minimize the total tardy time. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, a genetic algorithm using an effective dispatching method is proposed. The performance of the proposed genetic algorithm is evaluated using several randomly generated examples.

• 한국경영과학회지
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• 제33권1호
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• pp.117-129
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• 2008

Make-to-order manufacturers with multiple plants at multiple sites need to have the ability to quickly determine which plant will produce which customer order to meet the due date and minimize the transportation cost from the plants to the customer. Balancing the work loads and minimizing setups and make-span are also of great concern. Solving such scheduling problems usually takes a long time. We propose a new approach, which we call 'preprocessing', for resolving such complex problems. In preprocessing scheme, a 'good' a priori schedule is prepared and maintained using unconfirmed order information. Upon the confirmation of orders. the preprocessed schedule is quickly modified to obtain the final schedule. We present a preprocessing solution algorithm for multi-site constraint scheduling problem (MSCSP) using genetic algorithm; and conduct computational experiments to evaluate the performance of the algorithm.