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Unit Commitment Problem (UCP) is considered as a nonlinear mixed-integer combinatorial highly constrained optimization problem divided on two sub problems: binary UC scheduling and economic dispatch (ED). UCP is used to determine the appropriate operational scheduling of the units' production to satisfy the expected consumption at every hour interval under different constraints. In the last decades,...
Healthcare staff routing to provide healthcare service to the patients is one of the real-world scheduling problems similar to multiple travelling salesman problems (MTSP). Healthcare staff members provide daily medical services at patients' homes. The service provider authority has to schedule these staff in an effective and efficient way so that it achieves the minimum total cost. The aim of this...
This study addresses the efficiency of multiple threads Tabu search (TS) in solving scheduling problems. Nowadays, most desktop personal computers equip with multicore CPU. It is possible to achieve parallel searching strategy on a desktop computer. A problem of scheduling, which minimizes the total tardiness of a set of jobs to be scheduled on parallel identical machines, is presented as an example...
There is an interest in search algorithms capable of learning and adapting their behaviour while solving a given problem. A hyper-heuristic operates on a set of predefined heuristics and applies a machine learning technique to predict which heuristic is the most effective to apply at a given point in time. Thompson Sampling is a machine learning mechanism interacting with the search environment to...
The Multi-Mode Resource-Constrained Project Scheduling Problem (MRCPSP) is a generalization of the well known Resource-Constrained Project Scheduling Problem (RCPSP). The most common exact approaches for solving this problem are based on branch-and-bound algorithms, mixed integer linear programming and Boolean satisfiability (SAT). In this paper, we present a new exact approach for solving this problem,...
An alteration of the job shop scheduling problem, concerning advertisement scheduling on digital advertisement spaces, is presented. Dispatching Rules (DR), Iterated Local Search (ILS) and Genetic Algorithms (GA) are discussed and applied to the problem space. The results show that ILS is the best performing heuristic, and surpasses the other heuristics especially in large problem spaces (≥ 100 machines,...
This paper presents an improvement cuckoo search (ICS) algorithm for minimizing the project duration of the resource-constrained project scheduling problem with generalized precedence relations (RCPSP/max). The ICS algorithm is designed as follows, each individual is coded based on the priority of activity for scheduling as to be in a form which is suitable for matching the characteristics of Lévy...
The Freeze-Tag Problem is a problem in swarm robotics. The problem goes as this: there are n robots; Of these, n-1 ones are “asleep” or in “standby mode” in the beginning of the problem and only one robot is "awake". Only awake robots can move and the asleep ones are stationary. Once an awake robot touches an asleep robot by going to its exact place, the asleep robot awakens and becomes...
In this paper, we propose a new time-dependent heu-ristic algorithm for post enrolment-based course timetabling prob-lem. The algorithm operates in two stages: a constructive phase is proposed to insert events into the timetable whilst obeying most hard constraints, and a hill-climbing phase is designed to ensure the timetable meeting all the hard constraints. Each stage is allocated a time limit...
The optimization of test task scheduling problem (TTSP) is an important issue in automatic test system (ATS). TTSP is a complex combination optimization problem and includes two sub-problems. They are test task sequencing and test scheme combination. According to the characteristic of TTSP, a non-integrated algorithm based on estimation of distribution algorithm and Tabu Search (EDA-TS) is proposed...
In this paper, we tackle the Energy-Flexible Flow Shop Scheduling (EnFFS) problem, a multi-objective optimization problem focused on the minimization of both the overall completion time C and the global energy consumption E of the solutions. The tackled problem is an extension of the Flexible Flow-Shop Scheduling problem where each activity in a job has a set of possible execution modes with different...
Engine control applications include software tasks that are triggered at predetermined angular values of the crankshaft, thus generating a computational workload that varies with the engine speed. To avoid overloads at high rotation speeds, these tasks are implemented to self adapt and reduce their computational demand by switching mode at given rotation speeds. For this reason, they are referred...
In this paper, two one rank cuckoo search algorithm (ORCSA) based methods are first proposed for solving the short-term hydrothermal scheduling (ST-HTS) problem. The main objective of the ST-HTS problem is to minimize total generation fuel cost over a schedule time while satisfying equality constraints including power balance equations, total water discharge constraint and inequality constraints including...
In this paper, we propose a differential evolution algorithm with local search to solve the resource investment project scheduling problems (RIPSPs), labeled as DELS-RIPSP. Project tardiness is not permitted during the process of optimization. DELS-RIPSP improves the population quality by changing existing chromosomes to those with better fitness using the local search operator in order to reduce...
Nurse Rostering Problem (NRP) is one of NP - hard combinatorial optimization problems about the distribution of medical resources. In the past, there have been several proposed methods like heuristic algorithms and algorithms based on establishing rigorous mathematical models. Especially, the hybrid algorithm combined integer programming and evolutionary algorithm (IP+EA) have been proved to be effective...
This paper describes a method that combines graph heuristics and hill climbing for addressing the examination timetable problem. In this approach, all exams are ordered with graph heuristic ordering approach and partial exams are considered for scheduling. These partial scheduled exams are then improved using hill climbing until all exams have been successfully scheduled. Various exam assignment values...
Hyper-heuristic (HH) is a higher level heuristic to choose from a set of heuristics applicable for the problem on hand. In this paper, a Harmony Search-based Hyper-heuristic (HSHH) approach is tested in solving nurse rostering problems (NRP). NRP is a complex scheduling problem of assigning given shifts to a given nurses. We test the proposed method by using the First International Nurse Rostering...
We address the permutation flow shop scheduling problem with sequence dependent setup times between jobs. Each job has its weight of importance as well as due date. The goal is to find sequence of jobs such that total weighted tardiness of jobs is minimized. Due to NP-Hard complexity of this problem, a hybrid meta-heuristic algorithm based on Harmony Search Algorithm is developed. In the proposed...
This paper describes an efficient exact algorithm to solve the Resource Constrained Project Scheduling Problem (RCPSP). We propose an original and efficient branch and price procedure which involves minimal interval order enumeration as well as constraint propagation and which is implemented with the help of the generic SCIP software. We perform tests on the famous PSPLIB instances which provide very...
This paper proposes a cuckoo search algorithm (CSA) using different distributions for solving short-term hydrothermal scheduling (ST-HTS) problem with cascaded hydropower plants. The CSA method is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems...
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