A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem

We consider the multi-mode resource-constrained project scheduling problem (MRCPSP), where a task has different execution modes characterized by different resource requirements. Due to the nonrenewable resources and the multiple modes, this problem is NP-hard; therefore, we implement an evolutionary algorithm looking for a feasible solution minimizing the makespan.     

Bilevel programming approach applied to the flow shop scheduling problem under fuzziness

This paper presents a fuzzy bilevel programming approach to solve the flow shop scheduling problem. The problem considered here differs from the standard form in that operators are assigned to the machines and imposing a hierarchy of two decision makers with fuzzy processing times. The shop owner considered higher level and assigns the jobs to the machines in order to minimize the flow time while the customer is the lower level and decides on a job schedule in order to minimize the makespan. In this paper, we use the concepts of tolerance membership function at each level to define a fuzzy decision model for generating optimal (satisfactory) solution for bilevel flow shop scheduling problem. A solution algorithm for solving this problem is given. Mathematics Subject Classification: 90C70, 90B36, 90C99     

Some new results on simulated annealing applied to the job shop scheduling problem

We present two results about heuristic solutions to the job shop scheduling problem (JSP). First, we show that the well-known analytical results on convergence of simulated annealing (SA) do not hold in the application to the JSP. We give a simple counterexample where the SA process converges against a suboptimal schedule. To overcome this problem at least heuristically, we present a new approach that uses a small population of SA runs in a genetic algorithm (GA) framework. The novel features are an adaptive temperature control that allows `reheating' of the SA and a new type of time-oriented crossover of schedules. Though the procedure uses only standard properties of the JSP it yields excellent results on the classical test examples.     

A subproblem-centric model and approach to the nurse scheduling problem

The number of hospitals in Japan exceeds 10,000, and every month nurses are scheduled to shifts in about 30,000 units in total. There is serious demand for automating this scheduling task. In this paper, we introduce a mathematical programming formulation of the nurse scheduling problem in Japan, and develop a meta-heuristic approach to solve the problem. This scheduling problem is a hard combinatorial problem due to tight constraints involving such factors as the skill level of a team, the need to balance workload among nurses, and the consideration of nurses' preferences, even though the number of the nurses to be scheduled is not large, at between 20 and 40. The performance of our approach is demonstrated by the successful solution of data taken from actual scheduling problems. The proposed model and approach can be adapted for the majority of hospitals in Japan, as well as for some hospitals in other countries, and is likely applicable to many other scheduling problems in the fields of business and logistics. Key words.nurse scheduling – block-angular problem – subproblem – integer programming – relaxation – tabu search – branch-and-boundMathematics Subject Classification (1991):20E28, 20G40, 20C20     

单油罐修理线的天车运送周期性排序问题的求解

作为机车油罐修理中的一个重要资源,天车的排序直接影响系统的生产率.本文研究了产品在系统的一边装载、而在另一边卸载的油罐单修理线的天车周期性排序问题.工件在每个工作台需要加工一定的时间,工作台之间没有缓冲工作台,一台天车用于工作站之间工件的运送,目标是对运送进行排序以极小化生产周期.为了求解这个问题,本文提出了一个混合整数线性规划模型,量化示例表明所提出的方法是有效的.     

Mathematical model for scheduling operations in cascaded continuous processing units

The scenario under consideration involves n cascaded continuous processing units responsible for processing m product lines. Each product line needs to be processed by all the units in the same sequence, and has dedicated finite capacity storage tanks before and after every processing unit. A unit can process only one product line at a time. Inputs for all the product lines arrive continuously and simultaneously on the input side of the first unit in the sequence. There are multiple intermediate due dates for the final products. An optimal schedule for the units calls for a trade-off among spillage costs, upliftment failure penalties and changeover costs. A mathematical model is developed for the purpose and the resulting MINLP is linearized using standard techniques. The MILP has been tested using GAMS for three units and three product lines as encountered in a refinery situation. The model could output optimal schedules for a ten day scheduling horizon within reasonable time.     

An integer programming model for hierarchical workforce scheduling problem

In this paper, an integer programming model for the hierarchical workforce problem under the compressed workweeks is developed. The model is based on the integer programming formulation developed by Billionnet [A. Billionnet, Integer programming to schedule a hierarchical workforce with variable demands, European Journal of Operational Research 114 (1999) 105–114] for the hierarchical workforce problem. In our model, workers can be assigned to alternative shifts in a day during the course of a week, whereas all workers are assigned to one shift type in Billionnet’s model. The main idea of this paper is to use compressed workweeks in order to save worker costs. This case is also suitable for the practice. The proposed model is illustrated on the Billionnet’s example problem and the obtained results are compared with the Billionnet’s model results.     

Mathematical model to analyze the flow and heat transfer problem in U-shaped geothermal exchangers

In this study, we propose a mathematical model for U-shaped geothermal heat exchangers based on the unsteady Navier–Stokes problem. In the numerical solution of this problem, we divide the exchanger into two computational domains: rectilinear pipes where the temperature field is computed analytically, and a U-curved pipe where solutions for both the flow and heat exchange are calculated using a numerical procedure based on the Galerkin finite elements method. The results of some numerical simulations are provided and used to study the performance of geothermal exchangers by assessing the effective energy produced. We also present a validation analysis based on experimental measurements obtained from a real geothermal exchanger.     

Mathematical model and efficient algorithms for object packing problem

The article is devoted to mathematical models and practical algorithms for solving the cutting and packing (C&P) problem. We review and further enhance the main tool of our studies – phi-functions. Those are constructed here for 2D and 3D objects (unlike other standard tools, such as No-Fit Polygons, which are restricted to the 2D geometry). We also demonstrate that in many realistic cases the phi-functions can be described by quite simple formulas without radicals and other complications. Lastly, a general solution strategy using the phi-functions is outlined and illustrated by several 2D and 3D examples.     

Methods to solve multi-skill project scheduling problem

This is a summary of the author’s PhD thesis supervised by P. Martineau and E. Néron and defended on 28 November 2006 at the Université François-Rabelais de Tours. The thesis is written in French, and is available upon request from the author. This work deals with the problem of scheduling a project. The activities of this project requires skills that may not be mastered by all persons involved. First of all, the problem is defined in the introduction part. Then we propose different methods to solve it: lower bounds in part 2, different heuristics and meta-heuristics in part 3, and finally a branch-and-bound procedure in the last part.     

New MIP model for multiprocessor scheduling problem with communication delays

In this paper we consider scheduling tasks on a multiprocessor system, taking into account communication delays. We propose a new Mixed Integer Program (MIP) formulation that drastically reduces both the number of variables and the number of constraints, when compared to the best mathematical programming formulations from the literature. In addition, we propose pre-processing procedures that generates cuts and bounds on all variables, reducing the solution space of the problem as well. Cuts are obtained by using forward and backward critical path method from project management field, while the upper bound is derived from the new greedy heuristic. Computational experience shows advantages of our approach.     

Mathematical programming applied to cement-plant and quarry operations

A large linear-programming model is developed that describes cement operations from the quarry to the market. Separate optimization of clinker composition and quarry scheduling leads to inconsistencies, thereby creating a need for simultaneous optimization. By including both problems and their interfaces in the mode, simultaneous optimization is accomplished. Other factors included in the model are equipment acquisition and assignment, hauling distances and capacities, plant capacities, market prices and demands, and operational costs. Optimization objectives are maximization of net present value, life of mine, or production. Time periods are organized so that long-range profits guide short-range scheduling. Computer implementation of the model is also discussed.     

The just-in-time scheduling problem in a flow-shop scheduling system

We study the problem of maximizing the weighted number of just-in-time (JIT) jobs in a flow-shop scheduling system under four different scenarios. The first scenario is where the flow-shop includes only two machines and all the jobs have the same gain for being completed JIT. For this scenario, we provide an O(n³) time optimization algorithm which is faster than the best known algorithm in the literature. The second scenario is where the job processing times are machine-independent. For this scenario, the scheduling system is commonly referred to as a proportionate flow-shop. We show that in this case, the problem of maximizing the weighted number of JIT jobs is NP-hard in the ordinary sense for any arbitrary number of machines. Moreover, we provide a fully polynomial time approximation scheme (FPTAS) for its solution and a polynomial time algorithm to solve the special case for which all the jobs have the same gain for being completed JIT. The third scenario is where a set of identical jobs is to be produced for different customers. For this scenario, we provide an O(n³) time optimization algorithm which is independent of the number of machines. We also show that the time complexity can be reduced to O(n log n) if all the jobs have the same gain for being completed JIT. In the last scenario, we study the JIT scheduling problem on m machines with a no-wait restriction and provide an O(mn²) time optimization algorithm.     

Error expansion for a first-order upwind difference scheme applied to a model convection-diffusion problem

A singularly perturbed convection–diffusion problem isconsidered. The problem is discretized using a simple first-orderupwind difference scheme on general meshes. We derive an expansionof the error of the scheme that enables uniform error boundswith respect to the perturbation parameter in the discrete maximumnorm for both a defect correction method and the Richardsonextrapolation technique. This generalizes and simplifies resultsobtained in earlier publications by Fröhner et al.(2001,Numer. Algorithms, 26, 281–299) and by Natividad &Stynes (2003, Appl. Numer. Math., 45, 315–329). Numericalexperiments complement our theoretical results.     

Reducing the feasible region to a scheduling problem

A special class of scheduling problems is considered. We consider cycle-free sets of fronts correspond to the orderings of a network. If the project is recourse-constrained, the same cycle-free set of fronts can correspond to different orderings. Some cycle-free sets of fronts can be subsets of others. The goal of the paper is to characterize maximal cycle-free sets of fronts because only those are essential for obtaining an optimal schedule.     

Applying tabu search to the job-shop scheduling problem

In this paper, we apply the tabu-search technique to the job-shop scheduling problem, a notoriously difficult problem in combinatorial optimization. We show that our implementation of this method dominates both a previous approach with tabu search and the other heuristics based on iterative improvements.Partially supported by research contracts MPI 40% and 60% of the Italian Ministry of University and Scientific Research.     

Operation and preventive maintenance scheduling for containerships: Mathematical model and solution algorithm

This paper considers the problem of determining operation and maintenance schedules for a containership equipped with various subsystems during its sailing according to a pre-determined navigation schedule. The operation schedule, which specifies working time of each subsystem, determines the due-date of each maintenance activity and the maintenance schedule specifies the actual start time of each maintenance activity. The main constraints are subsystem requirements, workforce availability, working time limitation, and inter-maintenance time. To represent the problem mathematically, a mixed integer programming model is developed. Then, due to the complexity of the problem, we suggest a heuristic algorithm that minimizes the sum of earliness and tardiness between the due-date and the actual start time for each maintenance activity. Computational experiments were done on various test instances and the results are reported. In particular, a case study was done on a real instance and a significant amount of improvement is reported over the experience based conventional method.     

A mathematical model and algorithms for the aircraft hangar maintenance scheduling problem

An aircraft hangar maintenance scheduling problem is studied, motivated by the aircraft heavy maintenance conducted in a hangar operated by an independent maintenance service company. The aircraft hangar maintenance scheduling problem in such context consists of determining a maintenance schedule with minimum penalty costs in fulfilling maintenance requests, and a series of hangar parking plans aligned with the maintenance schedule through the planning period. A mixed-integer linear programming (MILP) mathematical model, integrating the interrelations between the maintenance schedule and aircraft parking layout plans, is presented at first. In the model, the variation of parking capacity of the maintenance hangar and the blocking of the aircraft rolling in and out path are considered. Secondly, the model is enhanced by narrowing down the domain of the time-related decision variables to the possible rolling in and out operations time of each maintenance request. Thirdly, to obtain good quality feasible solutions for large scale instances, a rolling horizon approach incorporating the enhanced mathematical model is presented. The results of computational experiments are reported, showing: (i) the effectiveness of the event-based discrete time MILP model and (ii) the scalability of the rolling horizon approach that is able to provide good feasible solutions for large size instances covering a long planning period.     

A contribution to the stochastic flow shop scheduling problem

This paper deals with performance evaluation and scheduling problems in m machine stochastic flow shop with unlimited buffers. The processing time of each job on each machine is a random variable exponentially distributed with a known rate. We consider permutation flow shop. The objective is to find a job schedule which minimizes the expected makespan. A classification of works about stochastic flow shop with random processing times is first given. In order to solve the performance evaluation problem, we propose a recursive algorithm based on a Markov chain to compute the expected makespan and a discrete event simulation model to evaluate the expected makespan. The recursive algorithm is a generalization of a method proposed in the literature for the two machine flow shop problem to the m machine flow shop problem with unlimited buffers. In deterministic context, heuristics (like CDS [Management Science 16 (10) (1970) B630] and Rapid Access [Management Science 23 (11) (1977) 1174]) and metaheuristics (like simulated annealing) provide good results. We propose to adapt and to test this kind of methods for the stochastic scheduling problem. Combinations between heuristics or metaheuristics and the performance evaluation models are proposed. One of the objectives of this paper is to compare the methods together. Our methods are tested on problems from the OR-Library and give good results: for the two machine problems, we obtain the optimal solution and for the m machine problems, the methods are mutually validated.