On the Relationship Between Combinatorial and LP-Based Approaches to NP-Hard Scheduling Problems

Author(s):  
R. N. Uma ◽  
Joel Wein
2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ruey-Maw Chen ◽  
Frode Eika Sandnes

The multimode resource-constrained project scheduling problem (MRCPSP) has been confirmed to be an NP-hard problem. Particle swarm optimization (PSO) has been efficiently applied to the search for near optimal solutions to various NP-hard problems. MRCPSP involves solving two subproblems: mode assignment and activity priority determination. Hence, two PSOs are applied to each subproblem. A constriction PSO is proposed for the activity priority determination while a discrete PSO is employed for mode assignment. A least total resource usage (LTRU) heuristic and minimum slack (MSLK) heuristic ensure better initial solutions. To ensure a diverse initial collection of solutions and thereby enhancing the PSO efficiency, a best heuristic rate (HR) is suggested. Moreover, a new communication topology with random links is also introduced to prevent slow and premature convergence. To verify the performance of the approach, the MRCPSP benchmarks in PSPLIB were evaluated and the results compared to other state-of-the-art algorithms. The results demonstrate that the proposed algorithm outperforms other algorithms for the MRCPSP problems. Finally, a real-world man-day project scheduling problem (MDPSP)—a MRCPSP problem—was evaluated and the results demonstrate that MDPSP can be solved successfully.


2018 ◽  
Vol 61 (2) ◽  
pp. 252-271 ◽  
Author(s):  
Megan Dewar ◽  
David Pike ◽  
John Proos

AbstractIn this paper we consider two natural notions of connectivity for hypergraphs: weak and strong. We prove that the strong vertex connectivity of a connected hypergraph is bounded by its weak edge connectivity, thereby extending a theorem of Whitney from graphs to hypergraphs. We find that, while determining a minimum weak vertex cut can be done in polynomial time and is equivalent to finding a minimum vertex cut in the 2-section of the hypergraph in question, determining a minimum strong vertex cut is NP-hard for general hypergraphs. Moreover, the problem of finding minimum strong vertex cuts remains NP-hard when restricted to hypergraphs with maximum edge size at most 3. We also discuss the relationship between strong vertex connectivity and the minimum transversal problem for hypergraphs, showing that there are classes of hypergraphs for which one of the problems is NP-hard, while the other can be solved in polynomial time.


2021 ◽  
Vol 47 ◽  
Author(s):  
Edgaras Šakurovas ◽  
Narimantas Listopadskis

Genetic algorithms are widely used in various mathematical and real world problems. They are approximate metaheuristic algorithms, commonly used for solving NP-hard problems in combinatorial optimisation. Industrial scheduling is one of the classical NP-hard problems. We analyze three classical industrial scheduling problems: job-shop, flow-shop and open-shop. Canonical genetic algorithm is applied for those problems varying its parameters. We analyze some aspects of parameters such as selecting optimal parameters of algorithm, influence on algorithm performance. Finally, three strategies of algorithm – combination of parameters and new conceptualmodel of genetic algorithm are proposed.


2013 ◽  
Vol 816-817 ◽  
pp. 1133-1139
Author(s):  
Nasir Mehmood ◽  
Muhammad Umer ◽  
Ahmad Riaz

Ant Colony Optimization (ACO) is based on swarm intelligence and it is a constructive meta-heuristic which was first presented in 1991. Job Shop Scheduling Problem (JSSP) is very important problem of the manufacturing industry. JSSP is a combinatorial optimization problem which is NP-hard. The exact solution of NP-hard problem is very difficult to find. Therefore heuristics approach is the best approach for such problems. This paper shall overview the application of ant colony optimization on JSSP and Flexible Job Shop Scheduling problems (FJSSP). This paper shalll cover the major areas in which researchers have worked and it shall also recommend the future area of research in the light of this overview. This paper will also cover the quantitative analysis of the research papers which are considered in this survey. Based upon this survey some conclusions are drawn in the end.The significance of this paper is that it has covered all the efforts and major researches in the area of ACO application on JSSP and FJSSP through the inception of ACO metaheuristics. This enables the researchers and scheduling experts to overview chronologically the development of ACO on JSSP and FJSSP.


2016 ◽  
Vol 08 (04) ◽  
pp. 1650058 ◽  
Author(s):  
Ming Liu ◽  
Shijin Wang ◽  
Feng Chu ◽  
Yinfeng Xu

This paper investigates the quay crane scheduling problem (QCSP) at container ports, subject to arbitrary precedence constraint among vessel container tasks. Differing from classic machine scheduling problems, noncrossing constraint for quay cranes must be satisfied. This is because quay cranes work in parallel and they travel on a same rail (along the berth), to perform container unloading and loading tasks for vessels. Precedence relation in an arbitrary form is rarely investigated in the literature, however, it may be originated from reefers or dangerous cargo which requires high priority of processing, and yard stacking plan. We present the computational complexity for several problem variations. In particular, we show the QCSP, even without precedence constraint, is strongly NP-hard. This complexity result improves the state-of-the-art, in which the same problem is shown to be NP-hard in the ordinary sense. Besides, we also prove that for two parallel quay cranes, if the processing times of container tasks are ones and twos, then this scheduling problem is NP-hard. This result implies that the QCSP with arbitrary precedence constraint is very difficult to solve. A genetic algorithm is proposed to obtain near-optimal solutions. Computational experiments demonstrate the efficiency.


2017 ◽  
Vol 15 (3) ◽  
pp. 16-19
Author(s):  
L. Kirilov ◽  
V. Guliashki

Abstract The flexible job shop problems (FJSP) are an important class of scheduling problems and they have a significant practical value. Unfortunately it is not easy to solve job shop problems and in particular FJSPs because they are NP-hard problems. In this paper we propose a method for generating a set of feasible schedules for a given FJSP.


Sign in / Sign up

Export Citation Format

Share Document