Qinghua Wu

Continuous p-dispersion problems with and without boundary constraints are NP-hard optimization problems with numerous real-world applications, notably in facility location and circle packing, which are widely studied in mathematics and operations research. In this work, we concentrate on general cases with a nonconvex multiply connected region tha...

The software and data in this repository are a snapshot of the software and data that were used in the research reported in the paper An efficient optimization model and tabu search-based global optimization approach for continuous p-dispersion problem by L.J. Lai, Z.H. Lin, J.K. Hao, and Q.H. Wu.

The knapsack problem (KP) with forfeits is a generalized KP that aims to select some items, among a set of candidate items, to maximize a profit function without exceeding the knapsack capacity. Moreover, a forfeit cost is incurred and deducted from the profit function when both incompatible items are placed in the knapsack. This problem is a relev...

Continuous p-dispersion problems with and without boundary constraints are NP-hard optimization problems with numerous real-world applications, notably in facility location and circle packing, which are widely studied in mathematics and operations research. In this work, we concentrate on general cases with a non-convex multiply-connected region th...

The cumulative capacitated vehicle routing problem with single (CCVRP) or multiple depots (MDCCVRP) is a variant of the popular capacitated vehicle routing problem. Instead of minimizing the total travel time, the objective here is to minimize the sum of all customers’ waiting times. This problem has a variety of real-world applications, especially...

The Hamiltonian p‐median problem consists of finding p(p$$ p $$ is given) non‐intersecting Hamiltonian cycles in a complete edge‐weighted graph such that each cycle visits at least three vertices and each vertex belongs to exactly one cycle, while minimizing the total cost of pcycles. In this work, we present an effective and scalable hybrid geneti...

The orienteering problem (OP) and prize‐collecting traveling salesman problem (PCTSP) are two typical TSPs with profits, in which each vertex has a profit and the goal is to visit several vertices to optimize the collected profit and travel costs. The OP aims to collect the maximum profit without exceeding the given travel cost. The PCTSP seeks to...

The cyclic cutwidth minimization problem (CCMP) is a graph layout problem that involves embedding a graph onto a circle to minimize the maximum cutwidth of the graph. In this paper, we present breakout local search (BLS) for solving CCMP, which combines a dedicated local search procedure to discover high-quality local optimal solutions and an adapt...

The Clustered Traveling Salesman Problem (CTSP) is a variant of the popular Traveling Salesman Problem (TSP) arising from a number of real-life applications. In this work, we explore a transformation approach that solves the CTSP by converting it to the well-studied TSP. For this purpose, we first investigate a technique to convert a CTSP instance...

The capacitated minimum spanning tree (CMST) problem is a fundamental problem in telecommunication network design. Given a central node and a set of remote terminal nodes with specified demands for traffic, the goal of CMST is to find a minimum cost spanning tree (network) such that the traffic on any arc of the network satisfies the capacity const...

The minimum load coloring problem (MLCP) is an important NP-complete problem arising in Wavelength Division Multiplexing (WDM) with a wide application in broadcast WDM networks. In this work, we present an integer programming model to formulate MLCP and provide a reinforcement learning based tabu search to approximately solve this problem. The prop...

The gate assignment problem (GAP) is an important task in airport management. This study investigates an original probability learning based heuristic algorithm for solving the problem. The proposed algorithm relies on a mixed search strategy exploring both feasible and infeasible solutions with the tabu search method and employs a reinforcement le...

Given a graph and a threshold gamma, the maximum quasi-clique (MQC) problem is to find a maximum cardinality subset of vertices in the graph such that the edge density of a corresponding induced subgraph is not less than gamma. This problem istended version of the famous maximum clique problem, which arises in a various application domains and is k...

The colored traveling salesmen problem is a node routing problem with multiple salesmen, where the cities are divided into m exclusive city sets and one shared city set. The objective is to minimize the total traveling distance of m Hamiltonian circuits (routes) under the following constraints: each exclusive city is to be visited by the correspond...

Knapsack problems are useful models that can formulate many real-life applications. The generalized quadratic multiple knapsack problem (GQMKP) extends the well-known quadratic multiple knapsack problem by taking into account setups and knapsack preference of the items. In this study, an efficient hybrid evolutionary search algorithm (HESA) is prop...

Clustering is a common task in data mining for constructing well-separated groups (clusters) from a large set of data points. The balanced minimum sum-of-squares clustering problem is a variant of the classic minimum sum-of-squares clustering (MSSC) problem and arises from broad real-life applications where the cardinalities of any two clusters dif...

Covering salesman problem (CSP) is an extension of the popular traveling salesman problem (TSP) arising from a number of real-life applications. Given a set of vertices and a predetermined coverage radius associated with each vertex, the goal of CSP is to find a minimum cost Hamiltonian cycle across a subset of vertices, such that each unvisited ve...

The generalized bike-sharing rebalancing problem (BRP) entails driving a fleet of capacitated vehicles to rebalance bicycles among bike-sharing system stations at a minimum cost. To solve this NP-hard problem, we present a highly effective memetic algorithm that combines (i) a randomized greedy construction method for initial solution generation, (...

The Clustered Traveling Salesman Problem (CTSP) is a variant of the popular Traveling Salesman Problem (TSP) arising from a number of real-life applications. In this work, we explore an uncharted solution approach that solves the CTSP by transforming it to the well-studied TSP. For this purpose, we first investigate a technique to convert a CTSP in...

The edge minimum sum-of-squares clustering problem (E-MSSC) aims at finding p prototypes such that the sum of squares of distances from a set of vertices to their closest prototype is minimized, where a prototype is either a vertex or an interior point of an edge. This paper proposes a highly effective memetic algorithm for E-MSSC that combines a d...

Composing medical crews with equity and efficiency is an important practical problem commonly arising from health care system management. This work presents the first hybrid memetic algorithm for this problem. The proposed approach integrates an original backbone-based crossover for generating promising offspring solutions and a tabu search based l...

In this paper, we study the multi-period inspector scheduling problem (MPISP). This problem aims to determine a set of routes for a team of inspectors performing inspection jobs in different locations across multiple days, with the objective of maximizing the total workloads that the inspectors undertake. Since an inspector can only perform inspect...

Given a simple undirected graph G = (V, E) and a constant γ, the γ-quasi-clique is defined as a subset of vertices that induces a subgraph with the edge density of at least γ. The maximum γ-quasi-clique problem (MQCP) is to find a γ-quasi-clique of the maximum cardinality in G. This problem has many practical applications, especially in social netw...

We propose an effective multi-wave algorithm organized in multiple search phases for the max-mean dispersion problem, which offers enhancement of neighborhood search algorithms by incorporating the notion of persistent attractiveness in memory based strategies. In each wave, a vertical phase and a horizontal phase are first alternated to reach a bo...

Given an undirected graph G=(V,E) and a positive integer k, an equitable legal k-coloring of G is a partition of the vertex set V into k disjoint independent sets such that the cardinalities of any two independent sets differ by one at most. The equitable coloring problem is to find the smallest k for which an equitable legal k-coloring exists. The...

The Traveling Repairman Problem with Profits is a node routing problem, where a repairman visits a subset of nodes of a weighted graph in order to maximize the collected time-dependent profits. In this work, we present the first population-based hybrid evolutionary search algorithm for solving the problem that combines: (i) a randomized greedy cons...

Given a weighted graph, the capacitated clustering problem (CCP) is to partition a set of nodes into a given number of distinct clusters (or groups) with restricted capacities, while maximizing the sum of edge weights corresponding to two nodes from the same cluster. CCP is an NP-hard problem with many relevant applications. This paper proposes two...

The multi-commodity pickup-and-delivery traveling salesman problem (m-PDTSP) is a variant of the classic traveling salesman problem with pickup and delivery. It arises from a number of real-life applications where a capacitated vehicle services a set of customers that provide or require certain amounts of different commodities. In this paper, we pr...

The Weighted Vertex Coloring Problem of a vertex weighted graph is to partition the vertex set into k disjoint independent sets such that the sum of the costs of these sets is minimized, where the cost of each set is given by the maximum weight of a vertex (representative) in that set. To solve this NP-hard problem, we present the adaptive feasible...

The equitable coloring problem is a variant of the classical graph coloring problem that arises from a number of real-life applications where the cardinality of color classes must be balanced. In this paper, we present a highly effective hybrid tabu search method for the problem. Based on three complementary neighborhoods, the algorithm alternates...

The pickup and delivery traveling salesman problem with FIFO loading (TSPPDF) is a variant of the classic traveling salesman problem with pickup and delivery arising from several practical applications where services have to be carried out in the first-in-first-out fashion. In this paper, we present a multi-restart iterative search approach (MIS) f...

The bipartite boolean quadratic programming problem with partitioned variables (BQP-PV) is an NP-hard combinatorial optimization problem that accommodates a variety of real-life applications. We propose an adaptive tabu search with strategic oscillation (ATS-SO) approach for BQP-PV, which employs a multi-pass search framework where each pass consis...

The Orienteering Problem with Mandatory Visits and Exclusionary Constraints (OPMVEC) is to visit a set of mandatory nodes (locations) and some optional nodes, while respecting the compatibility constraint between nodes and the maximum total time budget constraint. It is a variation of the classic orienteering problem that originates from a number o...

The Minimum Sum Coloring Problem (MSCP) is a relevant model tightly related to the classical vertex coloring problem (VCP). MSCP is known to be NP-hard, thus solving the problem for large graphs is particular challenging. Based on the general “reduce-and-solve” principle and inspired by the work for the VCP, we present an extraction and backward ex...

The Traveling Salesman Problem with Hotel Selection (TSPHS) is a variant of the classic Traveling Salesman Problem. It arises from a number of real-life applications where the maximum travel time for each “day trip” is limited. In this paper, we present a highly effective hybrid between dynamic programming and memetic algorithm for TSPHS. The main...

An equitable legal k-coloring of an undirected graph G = (V, E) is a partition of the vertex set V into k disjoint independent sets, such that the cardinalities of any two independent sets differ by at most one (this is called the equity constraint). As a variant of the popular graph coloring problem (GCP), the equitable coloring problem (ECP) invo...

This paper presents tabu search and memetic search algorithms for solving the minimum differential dispersion problem. The tabu search algorithm employs a neighborhood decomposition candidate list strategy and a rarely used solution-based tabu memory. Unlike the typical attribute-based tabu list, the solution-based tabu strategy leads to a more hig...

In recent years, the general binary quadratic programming (BQP) model has been widely applied to solve a number of combinatorial optimization problems. In this paper, we recast the maximum vertex weight clique problem (MVWCP) into this model which is then solved by a probabilistic tabu search algorithm designed for the BQP. Experimental results on...

Given a set of items to sell and a set of combinatorial bids, the Winner Determination Problem (WDP) in combinatorial auctions is to determine an allocation of items to bidders such that the auctioneer’s revenue is maximized while each item is allocated to at most one bidder. WDP is at the core of numerous relevant applications in multi-agent syste...

The power system islanding problem aims to divide the power system into several different islands after serious disturbances occur. The objective of this problem is to minimize the total generation-load imbalance of all islands while placing the coherent generators in the same island and maintaining the connectivity of each island. Two main challen...

This paper presents a tabu search based hybrid evolutionary algorithm (TSHEA) for solving the max-cut problem. The proposed algorithm integrates a distance-and-quality based solution combination operator and a tabu search procedure based on neighborhood combination of one-flip and constrained exchange moves. Comparisons with leading reference algor...

The maximum clique problem (MCP) is to determine in a graph a clique (i.e., a complete subgraph) of maximum cardinality. The MCP is notable for its capability of modeling other combinatorial problems and real-world applications. As one of the most studied NP-hard problems, many algorithms are available in the literature and new methods are continua...

Combinatorial auctions (CAs) where bidders can bid on combinations of items is an important model in many application areas. CAs attract more and more attention in recent years due to its relevance to fast growing electronic business applications. In this paper, we study the winner determination problem (WDP) in CAs which is known to be NP-hard and...

The Maximum Diversity Problem (MDP) consists in selecting a subset of m elements from a given set of n elements (n>m) in such a way that the sum of the pairwise distances between the m chosen elements is maximized. We present a hybrid metaheuristic algorithm (denoted by MAMDP) for MDP. The algorithm uses a dedicated crossover operator to generate n...

This paper presents an extraction and expansion approach for the graph coloring problem. The extraction phase transforms a large graph into a sequence of progressively smaller graphs by removing large independent sets from the graph. The expansion phase starts by generating an approximate coloring for the smallest graph in the sequence. Then it exp...

Given an undirected graph G=(V,E) with vertex set V={1,…,n} and edge set E⊆V×V. The maximum clique problem is to determine in G a clique (i.e., a complete subgraph) of maximum cardinality. This paper presents an effective algorithm for the maximum clique problem. The proposed multistart tabu search algorithm integrates a constrained neighborhood, a...

Given an undirected graph $G = (V,E)$ with a set $V$ of vertices and a set $E$ of edges, the minimum sum coloring problem (MSCP) is to find a legal vertex coloring of $G$, using colors represented by natural numbers $1, 2, . . .$ such that the total sum of the colors assigned to the vertices is minimized. This paper describes an approach based on t...

Given an undirected graph G=(V,E)G=(V,E) with weights on the edges, the max-bisection problem (MBP) is to find a partition of the vertex set VV into two subsets V1 and V2 of equal cardinality such that the sum of the weights of the edges crossing V1 and V2 is maximized. Relaxing the equal cardinality, constraint leads to the max-cut problem (MCP)....

Graph coloring is one of the most studied combinatorial optimization problems. This paper presents an improved extraction and expansion method (IE2COL), initially introduced in Wu and Hao (2012) [44]. IE2COL employs a forward independent set extraction strategy to reduce the initial graph GG. From the reduced graph, IE2COL triggers a backward color...

The max-cut problem is to partition the vertices of a weighted graph G=(V,E) into two subsets such that the weight sum of the edges crossing the two subsets is maximized. This paper presents a memetic max-cut algorithm (MACUT) that relies on a dedicated multi-parent crossover operator and a perturbation-based tabu search procedure. Experiments on 3...

Given an undirected graph G=(V,E), the minimum sum coloring problem (MSCP) is to find a legal vertex coloring of G, using colors represented by natural numbers (1,2,…) such that the total sum of the colors assigned to the vertices is minimized. In this paper, we present EXSCOL, a heuristic algorithm based on independent set extraction for this NP-h...

Given an undirected graph G=(V,E) with vertex set V={1,…,n} and edge set E⊆V×V. Let w:V→Z + be a weighting function that assigns to each vertex i∈V a positive integer. The maximum weight clique problem (MWCP) is to determine a clique of maximum weight. This paper introduces a tabu search heuristic whose key features include a combined neighborhood...

This paper presents an effective approach (EXTRACOL) to coloring large graphs. The proposed approach uses a preprocessing method to extract large independent sets from the graph and a memetic algorithm to color the residual graph. Each preprocessing application identifies, with a dedicated tabu search algorithm, a number of pairwise disjoint indepe...